id int32 0 165k | repo stringlengths 7 58 | path stringlengths 12 218 | func_name stringlengths 3 140 | original_string stringlengths 73 34.1k | language stringclasses 1
value | code stringlengths 73 34.1k | code_tokens list | docstring stringlengths 3 16k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 105 339 |
|---|---|---|---|---|---|---|---|---|---|---|---|
29,000 | Waikato/moa | moa/src/main/java/moa/clusterers/outliers/AnyOut/util/DataSet.java | DataSet.getVariances | public double[] getVariances() {
double N = this.size();
double[] LS = new double[this.getNrOfDimensions()];
double[] SS = new double[this.getNrOfDimensions()];
double[] tmpFeatures;
double[] variances = new double[this.getNrOfDimensions()];
for (DataObject dataObject : dataList) {
tmpFeatures = d... | java | public double[] getVariances() {
double N = this.size();
double[] LS = new double[this.getNrOfDimensions()];
double[] SS = new double[this.getNrOfDimensions()];
double[] tmpFeatures;
double[] variances = new double[this.getNrOfDimensions()];
for (DataObject dataObject : dataList) {
tmpFeatures = d... | [
"public",
"double",
"[",
"]",
"getVariances",
"(",
")",
"{",
"double",
"N",
"=",
"this",
".",
"size",
"(",
")",
";",
"double",
"[",
"]",
"LS",
"=",
"new",
"double",
"[",
"this",
".",
"getNrOfDimensions",
"(",
")",
"]",
";",
"double",
"[",
"]",
"S... | Calculates the variance of this data set for each dimension
@return double array containing the variance per dimension | [
"Calculates",
"the",
"variance",
"of",
"this",
"data",
"set",
"for",
"each",
"dimension"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/outliers/AnyOut/util/DataSet.java#L202-L223 |
29,001 | Waikato/moa | moa/src/main/java/com/yahoo/labs/samoa/instances/SparseInstanceData.java | SparseInstanceData.toDoubleArray | @Override
public double[] toDoubleArray() {
double[] array = new double[numAttributes()];
for (int i = 0; i < numValues(); i++) {
array[index(i)] = valueSparse(i);
}
return array;
} | java | @Override
public double[] toDoubleArray() {
double[] array = new double[numAttributes()];
for (int i = 0; i < numValues(); i++) {
array[index(i)] = valueSparse(i);
}
return array;
} | [
"@",
"Override",
"public",
"double",
"[",
"]",
"toDoubleArray",
"(",
")",
"{",
"double",
"[",
"]",
"array",
"=",
"new",
"double",
"[",
"numAttributes",
"(",
")",
"]",
";",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"numValues",
"(",
")",
";... | To double array.
@return the double[] | [
"To",
"double",
"array",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/com/yahoo/labs/samoa/instances/SparseInstanceData.java#L203-L210 |
29,002 | Waikato/moa | moa/src/main/java/moa/clusterers/outliers/AnyOut/AnyOutCore.java | AnyOutCore.calcC1 | private double calcC1(int objectId) {
int nrOfPreviousResults = previousOScoreResultList.get(objectId).size();
if (nrOfPreviousResults == 0) {
return 0.0;
}
int count=1;
double difSum_k = Math.abs(lastOScoreResult.get(objectId)-previousOScoreResultList.get(objectId).get(nrOfPreviousResults-1));
... | java | private double calcC1(int objectId) {
int nrOfPreviousResults = previousOScoreResultList.get(objectId).size();
if (nrOfPreviousResults == 0) {
return 0.0;
}
int count=1;
double difSum_k = Math.abs(lastOScoreResult.get(objectId)-previousOScoreResultList.get(objectId).get(nrOfPreviousResults-1));
... | [
"private",
"double",
"calcC1",
"(",
"int",
"objectId",
")",
"{",
"int",
"nrOfPreviousResults",
"=",
"previousOScoreResultList",
".",
"get",
"(",
"objectId",
")",
".",
"size",
"(",
")",
";",
"if",
"(",
"nrOfPreviousResults",
"==",
"0",
")",
"{",
"return",
"... | Calculates the Confidence on the basis of the standard deviation of previous OScore results
@return confidence | [
"Calculates",
"the",
"Confidence",
"on",
"the",
"basis",
"of",
"the",
"standard",
"deviation",
"of",
"previous",
"OScore",
"results"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/outliers/AnyOut/AnyOutCore.java#L234-L252 |
29,003 | Waikato/moa | moa/src/main/java/moa/gui/experimentertab/Summary.java | Summary.invertedSumariesPerMeasure | public void invertedSumariesPerMeasure( String path) {
int cont = 0;
int algorithmSize = this.streams.get(0).algorithm.size();
int streamSize = this.streams.size();
int measureSize = this.streams.get(0).algorithm.get(0).measures.size();
while (cont != measureSize) {
... | java | public void invertedSumariesPerMeasure( String path) {
int cont = 0;
int algorithmSize = this.streams.get(0).algorithm.size();
int streamSize = this.streams.size();
int measureSize = this.streams.get(0).algorithm.get(0).measures.size();
while (cont != measureSize) {
... | [
"public",
"void",
"invertedSumariesPerMeasure",
"(",
"String",
"path",
")",
"{",
"int",
"cont",
"=",
"0",
";",
"int",
"algorithmSize",
"=",
"this",
".",
"streams",
".",
"get",
"(",
"0",
")",
".",
"algorithm",
".",
"size",
"(",
")",
";",
"int",
"streamS... | Generates a latex summary, in which the rows are the datasets and the
columns the algorithms. | [
"Generates",
"a",
"latex",
"summary",
"in",
"which",
"the",
"rows",
"are",
"the",
"datasets",
"and",
"the",
"columns",
"the",
"algorithms",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/experimentertab/Summary.java#L155-L214 |
29,004 | Waikato/moa | moa/src/main/java/moa/gui/experimentertab/Summary.java | Summary.generateCSV | public void generateCSV() {
int cont = 0;
int algorithmSize = this.streams.get(0).algorithm.size();
int streamSize = this.streams.size();
int measureSize = this.streams.get(0).algorithm.get(0).measures.size();
while (cont != measureSize) {
String out... | java | public void generateCSV() {
int cont = 0;
int algorithmSize = this.streams.get(0).algorithm.size();
int streamSize = this.streams.size();
int measureSize = this.streams.get(0).algorithm.get(0).measures.size();
while (cont != measureSize) {
String out... | [
"public",
"void",
"generateCSV",
"(",
")",
"{",
"int",
"cont",
"=",
"0",
";",
"int",
"algorithmSize",
"=",
"this",
".",
"streams",
".",
"get",
"(",
"0",
")",
".",
"algorithm",
".",
"size",
"(",
")",
";",
"int",
"streamSize",
"=",
"this",
".",
"stre... | Generate a csv file for the statistical analysis. | [
"Generate",
"a",
"csv",
"file",
"for",
"the",
"statistical",
"analysis",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/experimentertab/Summary.java#L508-L558 |
29,005 | Waikato/moa | moa/src/main/java/moa/clusterers/dstream/DensityGrid.java | DensityGrid.getNeighbours | public ArrayList<DensityGrid> getNeighbours()
{
ArrayList<DensityGrid> neighbours = new ArrayList<DensityGrid>();
DensityGrid h;
int[] hCoord = this.getCoordinates();
for (int i = 0 ; i < this.dimensions ; i++)
{
hCoord[i] = hCoord[i]-1;
h = new DensityGrid(hCoord);
neighbours.add(h);
hCoo... | java | public ArrayList<DensityGrid> getNeighbours()
{
ArrayList<DensityGrid> neighbours = new ArrayList<DensityGrid>();
DensityGrid h;
int[] hCoord = this.getCoordinates();
for (int i = 0 ; i < this.dimensions ; i++)
{
hCoord[i] = hCoord[i]-1;
h = new DensityGrid(hCoord);
neighbours.add(h);
hCoo... | [
"public",
"ArrayList",
"<",
"DensityGrid",
">",
"getNeighbours",
"(",
")",
"{",
"ArrayList",
"<",
"DensityGrid",
">",
"neighbours",
"=",
"new",
"ArrayList",
"<",
"DensityGrid",
">",
"(",
")",
";",
"DensityGrid",
"h",
";",
"int",
"[",
"]",
"hCoord",
"=",
... | Generates an Array List of neighbours for this density grid by varying each coordinate
by one in either direction. Does not test whether the generated neighbours are valid as
DensityGrid is not aware of the number of partitions in each dimension.
@return an Array List of neighbours for this density grid | [
"Generates",
"an",
"Array",
"List",
"of",
"neighbours",
"for",
"this",
"density",
"grid",
"by",
"varying",
"each",
"coordinate",
"by",
"one",
"in",
"either",
"direction",
".",
"Does",
"not",
"test",
"whether",
"the",
"generated",
"neighbours",
"are",
"valid",
... | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/dstream/DensityGrid.java#L170-L190 |
29,006 | Waikato/moa | moa/src/main/java/moa/clusterers/dstream/DensityGrid.java | DensityGrid.getInclusionProbability | @Override
public double getInclusionProbability(Instance instance) {
for (int i = 0 ; i < this.dimensions ; i++)
{
if ((int) instance.value(i) != this.coordinates[i])
return 0.0;
}
return 1.0;
} | java | @Override
public double getInclusionProbability(Instance instance) {
for (int i = 0 ; i < this.dimensions ; i++)
{
if ((int) instance.value(i) != this.coordinates[i])
return 0.0;
}
return 1.0;
} | [
"@",
"Override",
"public",
"double",
"getInclusionProbability",
"(",
"Instance",
"instance",
")",
"{",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"this",
".",
"dimensions",
";",
"i",
"++",
")",
"{",
"if",
"(",
"(",
"int",
")",
"instance",
".",
... | Provides the probability of the argument instance belonging to the density grid in question.
@return 1.0 if the instance equals the density grid's coordinates; 0.0 otherwise. | [
"Provides",
"the",
"probability",
"of",
"the",
"argument",
"instance",
"belonging",
"to",
"the",
"density",
"grid",
"in",
"question",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/dstream/DensityGrid.java#L239-L248 |
29,007 | Waikato/moa | moa/src/main/java/moa/gui/experimentertab/Stream.java | Stream.readBuffer | public void readBuffer(List<String> algPath, List<String> algNames, List<Measure> measures) {
BufferedReader buffer = null;
for (int i = 0; i < algPath.size(); i++) {
try {
buffer = new BufferedReader(new FileReader(algPath.get(i)));
} catch (FileNotFoundException... | java | public void readBuffer(List<String> algPath, List<String> algNames, List<Measure> measures) {
BufferedReader buffer = null;
for (int i = 0; i < algPath.size(); i++) {
try {
buffer = new BufferedReader(new FileReader(algPath.get(i)));
} catch (FileNotFoundException... | [
"public",
"void",
"readBuffer",
"(",
"List",
"<",
"String",
">",
"algPath",
",",
"List",
"<",
"String",
">",
"algNames",
",",
"List",
"<",
"Measure",
">",
"measures",
")",
"{",
"BufferedReader",
"buffer",
"=",
"null",
";",
"for",
"(",
"int",
"i",
"=",
... | Read each algorithm file.
@param algPath
@param algNames
@param measures | [
"Read",
"each",
"algorithm",
"file",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/experimentertab/Stream.java#L65-L77 |
29,008 | Waikato/moa | moa/src/main/java/moa/streams/clustering/RandomRBFGeneratorEvents.java | RandomRBFGeneratorEvents.fireClusterChange | protected void fireClusterChange(long timestamp, String type, String message) {
// if we have no listeners, do nothing...
if (listeners != null && !listeners.isEmpty()) {
// create the event object to send
ClusterEvent event =
new ClusterEvent(this, timestamp, type , message);
// make... | java | protected void fireClusterChange(long timestamp, String type, String message) {
// if we have no listeners, do nothing...
if (listeners != null && !listeners.isEmpty()) {
// create the event object to send
ClusterEvent event =
new ClusterEvent(this, timestamp, type , message);
// make... | [
"protected",
"void",
"fireClusterChange",
"(",
"long",
"timestamp",
",",
"String",
"type",
",",
"String",
"message",
")",
"{",
"// if we have no listeners, do nothing...",
"if",
"(",
"listeners",
"!=",
"null",
"&&",
"!",
"listeners",
".",
"isEmpty",
"(",
")",
")... | Fire a ClusterChangeEvent to all registered listeners | [
"Fire",
"a",
"ClusterChangeEvent",
"to",
"all",
"registered",
"listeners"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/streams/clustering/RandomRBFGeneratorEvents.java#L940-L963 |
29,009 | Waikato/moa | moa/src/main/java/com/github/javacliparser/gui/ClassOptionEditComponent.java | ClassOptionEditComponent.notifyChangeListeners | protected void notifyChangeListeners() {
ChangeEvent e = new ChangeEvent(this);
for (ChangeListener l : changeListeners) {
l.stateChanged(e);
}
} | java | protected void notifyChangeListeners() {
ChangeEvent e = new ChangeEvent(this);
for (ChangeListener l : changeListeners) {
l.stateChanged(e);
}
} | [
"protected",
"void",
"notifyChangeListeners",
"(",
")",
"{",
"ChangeEvent",
"e",
"=",
"new",
"ChangeEvent",
"(",
"this",
")",
";",
"for",
"(",
"ChangeListener",
"l",
":",
"changeListeners",
")",
"{",
"l",
".",
"stateChanged",
"(",
"e",
")",
";",
"}",
"}"... | Notifies all registered change listeners that the options have changed. | [
"Notifies",
"all",
"registered",
"change",
"listeners",
"that",
"the",
"options",
"have",
"changed",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/com/github/javacliparser/gui/ClassOptionEditComponent.java#L137-L142 |
29,010 | Waikato/moa | moa/src/main/java/moa/gui/visualization/GraphScatter.java | GraphScatter.setGraph | public void setGraph(MeasureCollection[] measures, MeasureCollection[] stds,
double[] variedParamValues, Color[] colors) {
this.variedParamValues = variedParamValues;
super.setGraph(measures, stds, colors);
} | java | public void setGraph(MeasureCollection[] measures, MeasureCollection[] stds,
double[] variedParamValues, Color[] colors) {
this.variedParamValues = variedParamValues;
super.setGraph(measures, stds, colors);
} | [
"public",
"void",
"setGraph",
"(",
"MeasureCollection",
"[",
"]",
"measures",
",",
"MeasureCollection",
"[",
"]",
"stds",
",",
"double",
"[",
"]",
"variedParamValues",
",",
"Color",
"[",
"]",
"colors",
")",
"{",
"this",
".",
"variedParamValues",
"=",
"varied... | Draws a scatter graph based on the varied parameter and the measures.
@param measures list of measure collections, one for each task
@param stds standard deviation values
@param variedParamValues values of the varied parameter
@param colors color encodings for the different tasks | [
"Draws",
"a",
"scatter",
"graph",
"based",
"on",
"the",
"varied",
"parameter",
"and",
"the",
"measures",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/visualization/GraphScatter.java#L50-L54 |
29,011 | Waikato/moa | moa/src/main/java/moa/gui/visualization/GraphScatter.java | GraphScatter.scatter | private void scatter(Graphics g, int i) {
int height = getHeight();
int width = getWidth();
int x = (int)(((this.variedParamValues[i] - this.lower_x_value) / (this.upper_x_value - this.lower_x_value)) * width);
double value = this.measures[i].getLastValue(this.measureSelected);
if(Doub... | java | private void scatter(Graphics g, int i) {
int height = getHeight();
int width = getWidth();
int x = (int)(((this.variedParamValues[i] - this.lower_x_value) / (this.upper_x_value - this.lower_x_value)) * width);
double value = this.measures[i].getLastValue(this.measureSelected);
if(Doub... | [
"private",
"void",
"scatter",
"(",
"Graphics",
"g",
",",
"int",
"i",
")",
"{",
"int",
"height",
"=",
"getHeight",
"(",
")",
";",
"int",
"width",
"=",
"getWidth",
"(",
")",
";",
"int",
"x",
"=",
"(",
"int",
")",
"(",
"(",
"(",
"this",
".",
"vari... | Paint a dot onto the panel.
@param g graphics object
@param i index of the varied parameter | [
"Paint",
"a",
"dot",
"onto",
"the",
"panel",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/visualization/GraphScatter.java#L76-L100 |
29,012 | Waikato/moa | moa/src/main/java/moa/AbstractMOAObject.java | AbstractMOAObject.copy | public static MOAObject copy(MOAObject obj) {
try {
return (MOAObject) SerializeUtils.copyObject(obj);
} catch (Exception e) {
throw new RuntimeException("Object copy failed.", e);
}
} | java | public static MOAObject copy(MOAObject obj) {
try {
return (MOAObject) SerializeUtils.copyObject(obj);
} catch (Exception e) {
throw new RuntimeException("Object copy failed.", e);
}
} | [
"public",
"static",
"MOAObject",
"copy",
"(",
"MOAObject",
"obj",
")",
"{",
"try",
"{",
"return",
"(",
"MOAObject",
")",
"SerializeUtils",
".",
"copyObject",
"(",
"obj",
")",
";",
"}",
"catch",
"(",
"Exception",
"e",
")",
"{",
"throw",
"new",
"RuntimeExc... | This method produces a copy of an object.
@param obj object to copy
@return a copy of the object | [
"This",
"method",
"produces",
"a",
"copy",
"of",
"an",
"object",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/AbstractMOAObject.java#L62-L68 |
29,013 | Waikato/moa | moa/src/main/java/moa/gui/GUIDefaults.java | GUIDefaults.get | public static String get(String property, String defaultValue) {
return PROPERTIES.getProperty(property, defaultValue);
} | java | public static String get(String property, String defaultValue) {
return PROPERTIES.getProperty(property, defaultValue);
} | [
"public",
"static",
"String",
"get",
"(",
"String",
"property",
",",
"String",
"defaultValue",
")",
"{",
"return",
"PROPERTIES",
".",
"getProperty",
"(",
"property",
",",
"defaultValue",
")",
";",
"}"
] | returns the value for the specified property, if non-existent then the
default value.
@param property the property to retrieve the value for
@param defaultValue the default value for the property
@return the value of the specified property | [
"returns",
"the",
"value",
"for",
"the",
"specified",
"property",
"if",
"non",
"-",
"existent",
"then",
"the",
"default",
"value",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/GUIDefaults.java#L69-L71 |
29,014 | Waikato/moa | moa/src/main/java/moa/gui/GUIDefaults.java | GUIDefaults.getTabs | public static String[] getTabs() {
String[] result;
String tabs;
// read and split on comma
tabs = get("Tabs", "moa.gui.ClassificationTabPanel,moa.gui.RegressionTabPanel,moa.gui.MultiLabelTabPanel,moa.gui.MultiTargetTabPanel,moa.gui.clustertab.ClusteringTabPanel,moa.gui.outliertab.Outli... | java | public static String[] getTabs() {
String[] result;
String tabs;
// read and split on comma
tabs = get("Tabs", "moa.gui.ClassificationTabPanel,moa.gui.RegressionTabPanel,moa.gui.MultiLabelTabPanel,moa.gui.MultiTargetTabPanel,moa.gui.clustertab.ClusteringTabPanel,moa.gui.outliertab.Outli... | [
"public",
"static",
"String",
"[",
"]",
"getTabs",
"(",
")",
"{",
"String",
"[",
"]",
"result",
";",
"String",
"tabs",
";",
"// read and split on comma",
"tabs",
"=",
"get",
"(",
"\"Tabs\"",
",",
"\"moa.gui.ClassificationTabPanel,moa.gui.RegressionTabPanel,moa.gui.Mul... | returns an array with the classnames of all the additional panels to
display as tabs in the GUI.
@return the classnames | [
"returns",
"an",
"array",
"with",
"the",
"classnames",
"of",
"all",
"the",
"additional",
"panels",
"to",
"display",
"as",
"tabs",
"in",
"the",
"GUI",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/GUIDefaults.java#L134-L143 |
29,015 | Waikato/moa | moa/src/main/java/moa/gui/GUIDefaults.java | GUIDefaults.getFrameWidth | public static int getFrameWidth() {
int result;
String str;
str = get("FrameWidth", "1200");
try {
result = Integer.parseInt(str);
}
catch (Exception e) {
result = 1200;
}
return result;
} | java | public static int getFrameWidth() {
int result;
String str;
str = get("FrameWidth", "1200");
try {
result = Integer.parseInt(str);
}
catch (Exception e) {
result = 1200;
}
return result;
} | [
"public",
"static",
"int",
"getFrameWidth",
"(",
")",
"{",
"int",
"result",
";",
"String",
"str",
";",
"str",
"=",
"get",
"(",
"\"FrameWidth\"",
",",
"\"1200\"",
")",
";",
"try",
"{",
"result",
"=",
"Integer",
".",
"parseInt",
"(",
"str",
")",
";",
"... | Returns the width for the frame.
@return the width in pixel | [
"Returns",
"the",
"width",
"for",
"the",
"frame",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/GUIDefaults.java#L176-L187 |
29,016 | Waikato/moa | moa/src/main/java/moa/gui/GUIDefaults.java | GUIDefaults.main | public static void main(String[] args) {
Enumeration names;
String name;
Vector sorted;
System.out.println("\nMOA defaults:");
names = PROPERTIES.propertyNames();
// sort names
sorted = new Vector();
while (names.hasMoreElements()) {
sorted.a... | java | public static void main(String[] args) {
Enumeration names;
String name;
Vector sorted;
System.out.println("\nMOA defaults:");
names = PROPERTIES.propertyNames();
// sort names
sorted = new Vector();
while (names.hasMoreElements()) {
sorted.a... | [
"public",
"static",
"void",
"main",
"(",
"String",
"[",
"]",
"args",
")",
"{",
"Enumeration",
"names",
";",
"String",
"name",
";",
"Vector",
"sorted",
";",
"System",
".",
"out",
".",
"println",
"(",
"\"\\nMOA defaults:\"",
")",
";",
"names",
"=",
"PROPER... | only for testing - prints the content of the props file.
@param args commandline parameters - ignored | [
"only",
"for",
"testing",
"-",
"prints",
"the",
"content",
"of",
"the",
"props",
"file",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/GUIDefaults.java#L248-L270 |
29,017 | Waikato/moa | moa/src/main/java/moa/clusterers/clustream/ClustreamKernel.java | ClustreamKernel.inverseError | public static double inverseError(double x) {
double z = Math.sqrt(Math.PI) * x;
double res = (z) / 2;
double z2 = z * z;
double zProd = z * z2; // z^3
res += (1.0 / 24) * zProd;
zProd *= z2; // z^5
res += (7.0 / 960) * zProd;
zProd *= z2; // z^7
... | java | public static double inverseError(double x) {
double z = Math.sqrt(Math.PI) * x;
double res = (z) / 2;
double z2 = z * z;
double zProd = z * z2; // z^3
res += (1.0 / 24) * zProd;
zProd *= z2; // z^5
res += (7.0 / 960) * zProd;
zProd *= z2; // z^7
... | [
"public",
"static",
"double",
"inverseError",
"(",
"double",
"x",
")",
"{",
"double",
"z",
"=",
"Math",
".",
"sqrt",
"(",
"Math",
".",
"PI",
")",
"*",
"x",
";",
"double",
"res",
"=",
"(",
"z",
")",
"/",
"2",
";",
"double",
"z2",
"=",
"z",
"*",
... | Approximates the inverse error function. Clustream needs this.
@param z | [
"Approximates",
"the",
"inverse",
"error",
"function",
".",
"Clustream",
"needs",
"this",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/clustream/ClustreamKernel.java#L231-L255 |
29,018 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/BICO.java | BICO.bicoUpdate | protected void bicoUpdate(double[] x) {
assert (!this.bufferPhase && this.numDimensions == x.length);
// Starts with the global root node as the current root node
ClusteringTreeNode r = this.root;
int i = 1;
while (true) {
ClusteringTreeNode y = r.nearestChild(x);
// Checks if the point can not be added... | java | protected void bicoUpdate(double[] x) {
assert (!this.bufferPhase && this.numDimensions == x.length);
// Starts with the global root node as the current root node
ClusteringTreeNode r = this.root;
int i = 1;
while (true) {
ClusteringTreeNode y = r.nearestChild(x);
// Checks if the point can not be added... | [
"protected",
"void",
"bicoUpdate",
"(",
"double",
"[",
"]",
"x",
")",
"{",
"assert",
"(",
"!",
"this",
".",
"bufferPhase",
"&&",
"this",
".",
"numDimensions",
"==",
"x",
".",
"length",
")",
";",
"// Starts with the global root node as the current root node",
"Cl... | Inserts a new point into the ClusteringFeature tree.
@param x
the point | [
"Inserts",
"a",
"new",
"point",
"into",
"the",
"ClusteringFeature",
"tree",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/BICO.java#L294-L328 |
29,019 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/BICO.java | BICO.rebuild | protected void rebuild() {
// Checks if the number of nodes in the tree exceeds the maximum number
while (this.rootCount > this.maxNumClusterFeatures) {
// Doubles the global threshold
this.T *= 2.0;
this.root.setThreshold(calcRSquared(1));
// Adds all nodes to the ClusteringFeature tree again
Queue<... | java | protected void rebuild() {
// Checks if the number of nodes in the tree exceeds the maximum number
while (this.rootCount > this.maxNumClusterFeatures) {
// Doubles the global threshold
this.T *= 2.0;
this.root.setThreshold(calcRSquared(1));
// Adds all nodes to the ClusteringFeature tree again
Queue<... | [
"protected",
"void",
"rebuild",
"(",
")",
"{",
"// Checks if the number of nodes in the tree exceeds the maximum number",
"while",
"(",
"this",
".",
"rootCount",
">",
"this",
".",
"maxNumClusterFeatures",
")",
"{",
"// Doubles the global threshold",
"this",
".",
"T",
"*="... | If the number of ClusteringTreeNodes exceeds the maximum bound, the
global threshold T will be doubled and the tree will be rebuild with the
new threshold. | [
"If",
"the",
"number",
"of",
"ClusteringTreeNodes",
"exceeds",
"the",
"maximum",
"bound",
"the",
"global",
"threshold",
"T",
"will",
"be",
"doubled",
"and",
"the",
"tree",
"will",
"be",
"rebuild",
"with",
"the",
"new",
"threshold",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/BICO.java#L336-L355 |
29,020 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/BICO.java | BICO.bicoCFUpdate | protected void bicoCFUpdate(ClusteringTreeNode x) {
// Starts with the global root node as the current root node
ClusteringTreeNode r = this.root;
int i = 1;
while (true) {
ClusteringTreeNode y = r.nearestChild(x.getCenter());
// Checks if the node can not be merged to the current level
if (r.hasNoChil... | java | protected void bicoCFUpdate(ClusteringTreeNode x) {
// Starts with the global root node as the current root node
ClusteringTreeNode r = this.root;
int i = 1;
while (true) {
ClusteringTreeNode y = r.nearestChild(x.getCenter());
// Checks if the node can not be merged to the current level
if (r.hasNoChil... | [
"protected",
"void",
"bicoCFUpdate",
"(",
"ClusteringTreeNode",
"x",
")",
"{",
"// Starts with the global root node as the current root node",
"ClusteringTreeNode",
"r",
"=",
"this",
".",
"root",
";",
"int",
"i",
"=",
"1",
";",
"while",
"(",
"true",
")",
"{",
"Clu... | Inserts a ClusteringTreeNode into the ClusteringFeature tree.
@param x
the ClusteringTreeNode | [
"Inserts",
"a",
"ClusteringTreeNode",
"into",
"the",
"ClusteringFeature",
"tree",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/BICO.java#L363-L394 |
29,021 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/NearestNeighbourSearch.java | NearestNeighbourSearch.combSort11 | public static void combSort11(double arrayToSort[], int linkedArray[]) {
int switches, j, top, gap;
double hold1; int hold2;
gap = arrayToSort.length;
do {
gap=(int)(gap/1.3);
switch(gap) {
case 0:
gap = 1;
break;
case 9:
case 10:
gap=11;... | java | public static void combSort11(double arrayToSort[], int linkedArray[]) {
int switches, j, top, gap;
double hold1; int hold2;
gap = arrayToSort.length;
do {
gap=(int)(gap/1.3);
switch(gap) {
case 0:
gap = 1;
break;
case 9:
case 10:
gap=11;... | [
"public",
"static",
"void",
"combSort11",
"(",
"double",
"arrayToSort",
"[",
"]",
",",
"int",
"linkedArray",
"[",
"]",
")",
"{",
"int",
"switches",
",",
"j",
",",
"top",
",",
"gap",
";",
"double",
"hold1",
";",
"int",
"hold2",
";",
"gap",
"=",
"array... | sorts the two given arrays.
@param arrayToSort The array sorting should be based on.
@param linkedArray The array that should have the same ordering as
arrayToSort. | [
"sorts",
"the",
"two",
"given",
"arrays",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/NearestNeighbourSearch.java#L653-L685 |
29,022 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/NearestNeighbourSearch.java | NearestNeighbourSearch.quickSort | public static void quickSort(double[] arrayToSort, double[] linkedArray, int left, int right) {
if (left < right) {
int middle = partition(arrayToSort, linkedArray, left, right);
quickSort(arrayToSort, linkedArray, left, middle);
quickSort(arrayToSort, linkedArray, middle + 1, right);
}
} | java | public static void quickSort(double[] arrayToSort, double[] linkedArray, int left, int right) {
if (left < right) {
int middle = partition(arrayToSort, linkedArray, left, right);
quickSort(arrayToSort, linkedArray, left, middle);
quickSort(arrayToSort, linkedArray, middle + 1, right);
}
} | [
"public",
"static",
"void",
"quickSort",
"(",
"double",
"[",
"]",
"arrayToSort",
",",
"double",
"[",
"]",
"linkedArray",
",",
"int",
"left",
",",
"int",
"right",
")",
"{",
"if",
"(",
"left",
"<",
"right",
")",
"{",
"int",
"middle",
"=",
"partition",
... | performs quicksort.
@param arrayToSort the array to sort
@param linkedArray the linked array
@param left the first index of the subset
@param right the last index of the subset | [
"performs",
"quicksort",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/NearestNeighbourSearch.java#L734-L740 |
29,023 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.kNearestNeighbours | public Instances kNearestNeighbours(Instance target, int k) throws Exception {
checkMissing(target);
MyHeap heap = new MyHeap(k);
findNearestNeighbours(target, m_Root, k, heap, 0.0);
Instances neighbours = new Instances(m_Instances, (heap.size() + heap
.noOfKthNearest()));
m_DistanceLi... | java | public Instances kNearestNeighbours(Instance target, int k) throws Exception {
checkMissing(target);
MyHeap heap = new MyHeap(k);
findNearestNeighbours(target, m_Root, k, heap, 0.0);
Instances neighbours = new Instances(m_Instances, (heap.size() + heap
.noOfKthNearest()));
m_DistanceLi... | [
"public",
"Instances",
"kNearestNeighbours",
"(",
"Instance",
"target",
",",
"int",
"k",
")",
"throws",
"Exception",
"{",
"checkMissing",
"(",
"target",
")",
";",
"MyHeap",
"heap",
"=",
"new",
"MyHeap",
"(",
"k",
")",
";",
"findNearestNeighbours",
"(",
"targ... | Returns the k nearest neighbours of the supplied instance.
>k neighbours are returned if there are more than one
neighbours at the kth boundary.
@param target The instance to find the nearest neighbours for.
@param k The number of neighbours to find.
@return The k nearest neighbours (or >k if more there are th... | [
"Returns",
"the",
"k",
"nearest",
"neighbours",
"of",
"the",
"supplied",
"instance",
".",
">",
";",
"k",
"neighbours",
"are",
"returned",
"if",
"there",
"are",
"more",
"than",
"one",
"neighbours",
"at",
"the",
"kth",
"boundary",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L328-L359 |
29,024 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.update | public void update(Instance instance) throws Exception { // better to change
// to addInstance
if (m_Instances == null)
throw new Exception("No instances supplied yet. Have to call "
+ "setInstances(instances) with a set of Instances " + "f... | java | public void update(Instance instance) throws Exception { // better to change
// to addInstance
if (m_Instances == null)
throw new Exception("No instances supplied yet. Have to call "
+ "setInstances(instances) with a set of Instances " + "f... | [
"public",
"void",
"update",
"(",
"Instance",
"instance",
")",
"throws",
"Exception",
"{",
"// better to change",
"// to addInstance",
"if",
"(",
"m_Instances",
"==",
"null",
")",
"throw",
"new",
"Exception",
"(",
"\"No instances supplied yet. Have to call \"",
"+",
"\... | Adds one instance to the KDTree. This updates the KDTree structure to take
into account the newly added training instance.
@param instance the instance to be added. Usually the newly added instance in the
training set.
@throws Exception If the instance cannot be added. | [
"Adds",
"one",
"instance",
"to",
"the",
"KDTree",
".",
"This",
"updates",
"the",
"KDTree",
"structure",
"to",
"take",
"into",
"account",
"the",
"newly",
"added",
"training",
"instance",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L416-L424 |
29,025 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.checkMissing | protected void checkMissing(Instances instances) throws Exception {
for (int i = 0; i < instances.numInstances(); i++) {
Instance ins = instances.instance(i);
for (int j = 0; j < ins.numValues(); j++) {
if (ins.index(j) != ins.classIndex())
if (ins.isMissingSparse(j)) {
thr... | java | protected void checkMissing(Instances instances) throws Exception {
for (int i = 0; i < instances.numInstances(); i++) {
Instance ins = instances.instance(i);
for (int j = 0; j < ins.numValues(); j++) {
if (ins.index(j) != ins.classIndex())
if (ins.isMissingSparse(j)) {
thr... | [
"protected",
"void",
"checkMissing",
"(",
"Instances",
"instances",
")",
"throws",
"Exception",
"{",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"instances",
".",
"numInstances",
"(",
")",
";",
"i",
"++",
")",
"{",
"Instance",
"ins",
"=",
"instanc... | Checks if there is any instance with missing values. Throws an exception if
there is, as KDTree does not handle missing values.
@param instances the instances to check
@throws Exception if missing values are encountered | [
"Checks",
"if",
"there",
"is",
"any",
"instance",
"with",
"missing",
"values",
".",
"Throws",
"an",
"exception",
"if",
"there",
"is",
"as",
"KDTree",
"does",
"not",
"handle",
"missing",
"values",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L530-L542 |
29,026 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.checkMissing | protected void checkMissing(Instance ins) throws Exception {
for (int j = 0; j < ins.numValues(); j++) {
if (ins.index(j) != ins.classIndex())
if (ins.isMissingSparse(j)) {
throw new Exception("ERROR: KDTree can not deal with missing "
+ "values. Please run ReplaceMissingValues... | java | protected void checkMissing(Instance ins) throws Exception {
for (int j = 0; j < ins.numValues(); j++) {
if (ins.index(j) != ins.classIndex())
if (ins.isMissingSparse(j)) {
throw new Exception("ERROR: KDTree can not deal with missing "
+ "values. Please run ReplaceMissingValues... | [
"protected",
"void",
"checkMissing",
"(",
"Instance",
"ins",
")",
"throws",
"Exception",
"{",
"for",
"(",
"int",
"j",
"=",
"0",
";",
"j",
"<",
"ins",
".",
"numValues",
"(",
")",
";",
"j",
"++",
")",
"{",
"if",
"(",
"ins",
".",
"index",
"(",
"j",
... | Checks if there is any missing value in the given
instance.
@param ins The instance to check missing values in.
@throws Exception If there is a missing value in the
instance. | [
"Checks",
"if",
"there",
"is",
"any",
"missing",
"value",
"in",
"the",
"given",
"instance",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L551-L560 |
29,027 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.enumerateMeasures | public Enumeration enumerateMeasures() {
Vector<String> newVector = new Vector<String>();
newVector.addElement("measureTreeSize");
newVector.addElement("measureNumLeaves");
newVector.addElement("measureMaxDepth");
return newVector.elements();
} | java | public Enumeration enumerateMeasures() {
Vector<String> newVector = new Vector<String>();
newVector.addElement("measureTreeSize");
newVector.addElement("measureNumLeaves");
newVector.addElement("measureMaxDepth");
return newVector.elements();
} | [
"public",
"Enumeration",
"enumerateMeasures",
"(",
")",
"{",
"Vector",
"<",
"String",
">",
"newVector",
"=",
"new",
"Vector",
"<",
"String",
">",
"(",
")",
";",
"newVector",
".",
"addElement",
"(",
"\"measureTreeSize\"",
")",
";",
"newVector",
".",
"addEleme... | Returns an enumeration of the additional measure names.
@return an enumeration of the measure names | [
"Returns",
"an",
"enumeration",
"of",
"the",
"additional",
"measure",
"names",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L653-L659 |
29,028 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.getMeasure | public double getMeasure(String additionalMeasureName) {
if (additionalMeasureName.compareToIgnoreCase("measureMaxDepth") == 0) {
return measureMaxDepth();
} else if (additionalMeasureName.compareToIgnoreCase("measureTreeSize") == 0) {
return measureTreeSize();
} else if (additionalMeasureName.c... | java | public double getMeasure(String additionalMeasureName) {
if (additionalMeasureName.compareToIgnoreCase("measureMaxDepth") == 0) {
return measureMaxDepth();
} else if (additionalMeasureName.compareToIgnoreCase("measureTreeSize") == 0) {
return measureTreeSize();
} else if (additionalMeasureName.c... | [
"public",
"double",
"getMeasure",
"(",
"String",
"additionalMeasureName",
")",
"{",
"if",
"(",
"additionalMeasureName",
".",
"compareToIgnoreCase",
"(",
"\"measureMaxDepth\"",
")",
"==",
"0",
")",
"{",
"return",
"measureMaxDepth",
"(",
")",
";",
"}",
"else",
"if... | Returns the value of the named measure.
@param additionalMeasureName the name of
the measure to query for its value.
@return The value of the named measure
@throws IllegalArgumentException If the named measure
is not supported. | [
"Returns",
"the",
"value",
"of",
"the",
"named",
"measure",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L670-L681 |
29,029 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.centerInstances | public void centerInstances(Instances centers, int[] assignments, double pc)
throws Exception {
int[] centList = new int[centers.numInstances()];
for (int i = 0; i < centers.numInstances(); i++)
centList[i] = i;
determineAssignments(m_Root, centers, centList, assignments, pc);
} | java | public void centerInstances(Instances centers, int[] assignments, double pc)
throws Exception {
int[] centList = new int[centers.numInstances()];
for (int i = 0; i < centers.numInstances(); i++)
centList[i] = i;
determineAssignments(m_Root, centers, centList, assignments, pc);
} | [
"public",
"void",
"centerInstances",
"(",
"Instances",
"centers",
",",
"int",
"[",
"]",
"assignments",
",",
"double",
"pc",
")",
"throws",
"Exception",
"{",
"int",
"[",
"]",
"centList",
"=",
"new",
"int",
"[",
"centers",
".",
"numInstances",
"(",
")",
"]... | Assigns instances to centers using KDTree.
@param centers the current centers
@param assignments the centerindex for each instance
@param pc the threshold value for pruning.
@throws Exception If there is some problem
assigning instances to centers. | [
"Assigns",
"instances",
"to",
"centers",
"using",
"KDTree",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L701-L709 |
29,030 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.determineAssignments | protected void determineAssignments(KDTreeNode node, Instances centers,
int[] candidates, int[] assignments, double pc) throws Exception {
// reduce number of owners for current hyper rectangle
int[] owners = refineOwners(node, centers, candidates);
// only one owner
if (owners.length == 1) {
... | java | protected void determineAssignments(KDTreeNode node, Instances centers,
int[] candidates, int[] assignments, double pc) throws Exception {
// reduce number of owners for current hyper rectangle
int[] owners = refineOwners(node, centers, candidates);
// only one owner
if (owners.length == 1) {
... | [
"protected",
"void",
"determineAssignments",
"(",
"KDTreeNode",
"node",
",",
"Instances",
"centers",
",",
"int",
"[",
"]",
"candidates",
",",
"int",
"[",
"]",
"assignments",
",",
"double",
"pc",
")",
"throws",
"Exception",
"{",
"// reduce number of owners for curr... | Assigns instances to the current centers called candidates.
@param node The node to start assigning the instances from.
@param centers all the current centers.
@param candidates the current centers the method works on.
@param assignments the center index for each instance.
@param pc the threshold value for pruning.
@t... | [
"Assigns",
"instances",
"to",
"the",
"current",
"centers",
"called",
"candidates",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L722-L744 |
29,031 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.refineOwners | protected int[] refineOwners(KDTreeNode node, Instances centers,
int[] candidates) throws Exception {
int[] owners = new int[candidates.length];
double minDistance = Double.POSITIVE_INFINITY;
int ownerIndex = -1;
Instance owner;
int numCand = candidates.length;
double[] distance = new dou... | java | protected int[] refineOwners(KDTreeNode node, Instances centers,
int[] candidates) throws Exception {
int[] owners = new int[candidates.length];
double minDistance = Double.POSITIVE_INFINITY;
int ownerIndex = -1;
Instance owner;
int numCand = candidates.length;
double[] distance = new dou... | [
"protected",
"int",
"[",
"]",
"refineOwners",
"(",
"KDTreeNode",
"node",
",",
"Instances",
"centers",
",",
"int",
"[",
"]",
"candidates",
")",
"throws",
"Exception",
"{",
"int",
"[",
"]",
"owners",
"=",
"new",
"int",
"[",
"candidates",
".",
"length",
"]"... | Refines the ownerlist.
@param node The current tree node.
@param centers all centers
@param candidates the indexes of those centers that are candidates.
@return list of owners
@throws Exception If some problem occurs in refining. | [
"Refines",
"the",
"ownerlist",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L755-L807 |
29,032 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.distanceToHrect | protected double distanceToHrect(KDTreeNode node, Instance x) throws Exception {
double distance = 0.0;
Instance closestPoint = (Instance)x.copy();
boolean inside;
inside = clipToInsideHrect(node, closestPoint);
if (!inside)
distance = m_EuclideanDistance.distance(closestPoint, x);
return... | java | protected double distanceToHrect(KDTreeNode node, Instance x) throws Exception {
double distance = 0.0;
Instance closestPoint = (Instance)x.copy();
boolean inside;
inside = clipToInsideHrect(node, closestPoint);
if (!inside)
distance = m_EuclideanDistance.distance(closestPoint, x);
return... | [
"protected",
"double",
"distanceToHrect",
"(",
"KDTreeNode",
"node",
",",
"Instance",
"x",
")",
"throws",
"Exception",
"{",
"double",
"distance",
"=",
"0.0",
";",
"Instance",
"closestPoint",
"=",
"(",
"Instance",
")",
"x",
".",
"copy",
"(",
")",
";",
"bool... | Returns the distance between a point and an hyperrectangle.
@param node The current node from whose hyperrectangle
the distance is to be measured.
@param x the point
@return the distance
@throws Exception If some problem occurs in determining
the distance to the hyperrectangle. | [
"Returns",
"the",
"distance",
"between",
"a",
"point",
"and",
"an",
"hyperrectangle",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L819-L828 |
29,033 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.clipToInsideHrect | protected boolean clipToInsideHrect(KDTreeNode node, Instance x) {
boolean inside = true;
for (int i = 0; i < m_Instances.numAttributes(); i++) {
// TODO treat nominals differently!??
if (x.value(i) < node.m_NodeRanges[i][MIN]) {
x.setValue(i, node.m_NodeRanges[i][MIN]);
inside = fa... | java | protected boolean clipToInsideHrect(KDTreeNode node, Instance x) {
boolean inside = true;
for (int i = 0; i < m_Instances.numAttributes(); i++) {
// TODO treat nominals differently!??
if (x.value(i) < node.m_NodeRanges[i][MIN]) {
x.setValue(i, node.m_NodeRanges[i][MIN]);
inside = fa... | [
"protected",
"boolean",
"clipToInsideHrect",
"(",
"KDTreeNode",
"node",
",",
"Instance",
"x",
")",
"{",
"boolean",
"inside",
"=",
"true",
";",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"m_Instances",
".",
"numAttributes",
"(",
")",
";",
"i",
"++... | Finds the closest point in the hyper rectangle to a given point. Change the
given point to this closest point by clipping of at all the dimensions to
be clipped of. If the point is inside the rectangle it stays unchanged. The
return value is true if the point was not changed, so the the return value
is true if the poin... | [
"Finds",
"the",
"closest",
"point",
"in",
"the",
"hyper",
"rectangle",
"to",
"a",
"given",
"point",
".",
"Change",
"the",
"given",
"point",
"to",
"this",
"closest",
"point",
"by",
"clipping",
"of",
"at",
"all",
"the",
"dimensions",
"to",
"be",
"clipped",
... | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L842-L856 |
29,034 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.assignSubToCenters | public void assignSubToCenters(KDTreeNode node, Instances centers,
int[] centList, int[] assignments) throws Exception {
// todo: undecided situations
int numCent = centList.length;
// WARNING: assignments is "input/output-parameter"
// should not be null and the following should not happen
i... | java | public void assignSubToCenters(KDTreeNode node, Instances centers,
int[] centList, int[] assignments) throws Exception {
// todo: undecided situations
int numCent = centList.length;
// WARNING: assignments is "input/output-parameter"
// should not be null and the following should not happen
i... | [
"public",
"void",
"assignSubToCenters",
"(",
"KDTreeNode",
"node",
",",
"Instances",
"centers",
",",
"int",
"[",
"]",
"centList",
",",
"int",
"[",
"]",
"assignments",
")",
"throws",
"Exception",
"{",
"// todo: undecided situations",
"int",
"numCent",
"=",
"centL... | Assigns instances of this node to center. Center to be assign to is decided
by the distance function.
@param node The KDTreeNode whose instances are to be assigned.
@param centers all the input centers
@param centList the list of centers to work with
@param assignments index list of last assignments
@throws Exception ... | [
"Assigns",
"instances",
"of",
"this",
"node",
"to",
"center",
".",
"Center",
"to",
"be",
"assign",
"to",
"is",
"decided",
"by",
"the",
"distance",
"function",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L910-L933 |
29,035 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java | KDTree.setDistanceFunction | public void setDistanceFunction(DistanceFunction df) throws Exception {
if (!(df instanceof EuclideanDistance))
throw new Exception("KDTree currently only works with "
+ "EuclideanDistanceFunction.");
m_DistanceFunction = m_EuclideanDistance = (EuclideanDistance) df;
} | java | public void setDistanceFunction(DistanceFunction df) throws Exception {
if (!(df instanceof EuclideanDistance))
throw new Exception("KDTree currently only works with "
+ "EuclideanDistanceFunction.");
m_DistanceFunction = m_EuclideanDistance = (EuclideanDistance) df;
} | [
"public",
"void",
"setDistanceFunction",
"(",
"DistanceFunction",
"df",
")",
"throws",
"Exception",
"{",
"if",
"(",
"!",
"(",
"df",
"instanceof",
"EuclideanDistance",
")",
")",
"throw",
"new",
"Exception",
"(",
"\"KDTree currently only works with \"",
"+",
"\"Euclid... | sets the distance function to use for nearest neighbour search.
@param df the distance function to use
@throws Exception if not EuclideanDistance | [
"sets",
"the",
"distance",
"function",
"to",
"use",
"for",
"nearest",
"neighbour",
"search",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/neighboursearch/KDTree.java#L1066-L1071 |
29,036 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java | ClusteringTreeNode.count | @Deprecated
public int count() {
int count = (clusteringFeature != null) ? 1 : 0;
for (ClusteringTreeNode child : children) {
count += child.count();
}
return count;
} | java | @Deprecated
public int count() {
int count = (clusteringFeature != null) ? 1 : 0;
for (ClusteringTreeNode child : children) {
count += child.count();
}
return count;
} | [
"@",
"Deprecated",
"public",
"int",
"count",
"(",
")",
"{",
"int",
"count",
"=",
"(",
"clusteringFeature",
"!=",
"null",
")",
"?",
"1",
":",
"0",
";",
"for",
"(",
"ClusteringTreeNode",
"child",
":",
"children",
")",
"{",
"count",
"+=",
"child",
".",
... | Counts the elements in tree with this node as the root.
@deprecated
@return the number of elements | [
"Counts",
"the",
"elements",
"in",
"tree",
"with",
"this",
"node",
"as",
"the",
"root",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java#L70-L77 |
29,037 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java | ClusteringTreeNode.addToClustering | public Clustering addToClustering(Clustering clustering) {
if (center != null && getClusteringFeature() != null) {
clustering.add(getClusteringFeature().toCluster());
}
for (ClusteringTreeNode child : children) {
child.addToClustering(clustering);
}
return clustering;
} | java | public Clustering addToClustering(Clustering clustering) {
if (center != null && getClusteringFeature() != null) {
clustering.add(getClusteringFeature().toCluster());
}
for (ClusteringTreeNode child : children) {
child.addToClustering(clustering);
}
return clustering;
} | [
"public",
"Clustering",
"addToClustering",
"(",
"Clustering",
"clustering",
")",
"{",
"if",
"(",
"center",
"!=",
"null",
"&&",
"getClusteringFeature",
"(",
")",
"!=",
"null",
")",
"{",
"clustering",
".",
"add",
"(",
"getClusteringFeature",
"(",
")",
".",
"to... | Adds all ClusterFeatures of the tree with this node as the root to a
Clustering.
@param clustering
the Clustering to add the ClusterFeatures too.
@return the input Clustering | [
"Adds",
"all",
"ClusterFeatures",
"of",
"the",
"tree",
"with",
"this",
"node",
"as",
"the",
"root",
"to",
"a",
"Clustering",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java#L87-L95 |
29,038 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java | ClusteringTreeNode.addToClusteringCenters | public List<double[]> addToClusteringCenters(List<double[]> clustering) {
if (center != null && getClusteringFeature() != null) {
clustering.add(getClusteringFeature().toClusterCenter());
}
for (ClusteringTreeNode child : children) {
child.addToClusteringCenters(clustering);
}
return clustering;
} | java | public List<double[]> addToClusteringCenters(List<double[]> clustering) {
if (center != null && getClusteringFeature() != null) {
clustering.add(getClusteringFeature().toClusterCenter());
}
for (ClusteringTreeNode child : children) {
child.addToClusteringCenters(clustering);
}
return clustering;
} | [
"public",
"List",
"<",
"double",
"[",
"]",
">",
"addToClusteringCenters",
"(",
"List",
"<",
"double",
"[",
"]",
">",
"clustering",
")",
"{",
"if",
"(",
"center",
"!=",
"null",
"&&",
"getClusteringFeature",
"(",
")",
"!=",
"null",
")",
"{",
"clustering",
... | Adds all clustering centers of the ClusterFeatures of the tree with this
node as the root to a List of points.
@param clustering
the List to add the clustering centers too.
@return the input List | [
"Adds",
"all",
"clustering",
"centers",
"of",
"the",
"ClusterFeatures",
"of",
"the",
"tree",
"with",
"this",
"node",
"as",
"the",
"root",
"to",
"a",
"List",
"of",
"points",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java#L105-L113 |
29,039 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java | ClusteringTreeNode.printClusteringCenters | public void printClusteringCenters(Writer stream) throws IOException {
if (center != null && getClusteringFeature() != null) {
getClusteringFeature().printClusterCenter(stream);
}
for (ClusteringTreeNode child : children) {
child.printClusteringCenters(stream);
}
} | java | public void printClusteringCenters(Writer stream) throws IOException {
if (center != null && getClusteringFeature() != null) {
getClusteringFeature().printClusterCenter(stream);
}
for (ClusteringTreeNode child : children) {
child.printClusteringCenters(stream);
}
} | [
"public",
"void",
"printClusteringCenters",
"(",
"Writer",
"stream",
")",
"throws",
"IOException",
"{",
"if",
"(",
"center",
"!=",
"null",
"&&",
"getClusteringFeature",
"(",
")",
"!=",
"null",
")",
"{",
"getClusteringFeature",
"(",
")",
".",
"printClusterCenter"... | Writes all clustering centers of the ClusterFeatures of the tree with this
node as the root to a given stream.
@param stream
the stream
@throws IOException
If an I/O error occurs | [
"Writes",
"all",
"clustering",
"centers",
"of",
"the",
"ClusterFeatures",
"of",
"the",
"tree",
"with",
"this",
"node",
"as",
"the",
"root",
"to",
"a",
"given",
"stream",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java#L124-L131 |
29,040 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java | ClusteringTreeNode.nearestChild | public ClusteringTreeNode nearestChild(double[] pointA) {
assert (this.center.length == pointA.length);
double minDistance = Double.POSITIVE_INFINITY;
ClusteringTreeNode min = null;
for (ClusteringTreeNode node : this.getChildren()) {
double d = Metric.distance(pointA, node.getCenter());
if (d < minDistan... | java | public ClusteringTreeNode nearestChild(double[] pointA) {
assert (this.center.length == pointA.length);
double minDistance = Double.POSITIVE_INFINITY;
ClusteringTreeNode min = null;
for (ClusteringTreeNode node : this.getChildren()) {
double d = Metric.distance(pointA, node.getCenter());
if (d < minDistan... | [
"public",
"ClusteringTreeNode",
"nearestChild",
"(",
"double",
"[",
"]",
"pointA",
")",
"{",
"assert",
"(",
"this",
".",
"center",
".",
"length",
"==",
"pointA",
".",
"length",
")",
";",
"double",
"minDistance",
"=",
"Double",
".",
"POSITIVE_INFINITY",
";",
... | Searches for the nearest child node by comparing each representation.
@param pointA
to find the nearest child for
@return the child node which is the nearest | [
"Searches",
"for",
"the",
"nearest",
"child",
"node",
"by",
"comparing",
"each",
"representation",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java#L188-L200 |
29,041 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java | ClusteringTreeNode.addChild | public boolean addChild(ClusteringTreeNode e) {
assert (this.center.length == e.center.length);
return this.children.add(e);
} | java | public boolean addChild(ClusteringTreeNode e) {
assert (this.center.length == e.center.length);
return this.children.add(e);
} | [
"public",
"boolean",
"addChild",
"(",
"ClusteringTreeNode",
"e",
")",
"{",
"assert",
"(",
"this",
".",
"center",
".",
"length",
"==",
"e",
".",
"center",
".",
"length",
")",
";",
"return",
"this",
".",
"children",
".",
"add",
"(",
"e",
")",
";",
"}"
... | Adds a child node.
@param e
the child node to add
@return <code>true</code>
@see java.util.List#add(java.lang.Object) | [
"Adds",
"a",
"child",
"node",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/ClusteringTreeNode.java#L210-L213 |
29,042 | Waikato/moa | moa/src/main/java/moa/classifiers/meta/RCD.java | RCD.getPreviousClassifier | private ClassifierKS getPreviousClassifier(Classifier classifier,
List<Instance> instances) {
ExecutorService threadPool = Executors.newFixedThreadPool(this.threadSizeOption.getValue());
int SIZE = this.classifiers.size();
Map<Integer, Future<Double>> futures = new HashMap<>();
... | java | private ClassifierKS getPreviousClassifier(Classifier classifier,
List<Instance> instances) {
ExecutorService threadPool = Executors.newFixedThreadPool(this.threadSizeOption.getValue());
int SIZE = this.classifiers.size();
Map<Integer, Future<Double>> futures = new HashMap<>();
... | [
"private",
"ClassifierKS",
"getPreviousClassifier",
"(",
"Classifier",
"classifier",
",",
"List",
"<",
"Instance",
">",
"instances",
")",
"{",
"ExecutorService",
"threadPool",
"=",
"Executors",
".",
"newFixedThreadPool",
"(",
"this",
".",
"threadSizeOption",
".",
"g... | Searches for the classifier best suited for actual data. All statistical
tests are performed in parallel.
@param classifier Classifier to be added
@param instances Instances used to build the classifier
@return | [
"Searches",
"for",
"the",
"classifier",
"best",
"suited",
"for",
"actual",
"data",
".",
"All",
"statistical",
"tests",
"are",
"performed",
"in",
"parallel",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/meta/RCD.java#L244-L284 |
29,043 | Waikato/moa | moa/src/main/java/moa/clusterers/clustree/ClusKernel.java | ClusKernel.makeOlder | protected void makeOlder(long timeDifference, double negLambda) {
if (timeDifference == 0) {
return;
}
//double weightFactor = AuxiliaryFunctions.weight(negLambda, timeDifference);
assert (negLambda < 0);
assert (timeDifference > 0);
double weightFactor = Mat... | java | protected void makeOlder(long timeDifference, double negLambda) {
if (timeDifference == 0) {
return;
}
//double weightFactor = AuxiliaryFunctions.weight(negLambda, timeDifference);
assert (negLambda < 0);
assert (timeDifference > 0);
double weightFactor = Mat... | [
"protected",
"void",
"makeOlder",
"(",
"long",
"timeDifference",
",",
"double",
"negLambda",
")",
"{",
"if",
"(",
"timeDifference",
"==",
"0",
")",
"{",
"return",
";",
"}",
"//double weightFactor = AuxiliaryFunctions.weight(negLambda, timeDifference);",
"assert",
"(",
... | Make this cluster older. This means multiplying weighted N, LS and SS
with a weight factor given by the time difference and the parameter
negLambda.
@param timeDifference The time elapsed between this current update and
the last one.
@param negLambda | [
"Make",
"this",
"cluster",
"older",
".",
"This",
"means",
"multiplying",
"weighted",
"N",
"LS",
"and",
"SS",
"with",
"a",
"weight",
"factor",
"given",
"by",
"the",
"time",
"difference",
"and",
"the",
"parameter",
"negLambda",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/clustree/ClusKernel.java#L114-L129 |
29,044 | Waikato/moa | moa/src/main/java/moa/clusterers/clustree/ClusKernel.java | ClusKernel.overwriteOldCluster | protected void overwriteOldCluster(ClusKernel other) {
this.totalN = other.totalN;
this.N = other.N;
//AuxiliaryFunctions.overwriteDoubleArray(this.LS, other.LS);
//AuxiliaryFunctions.overwriteDoubleArray(this.SS, other.SS);
assert (LS.length == other.LS.length);
System.a... | java | protected void overwriteOldCluster(ClusKernel other) {
this.totalN = other.totalN;
this.N = other.N;
//AuxiliaryFunctions.overwriteDoubleArray(this.LS, other.LS);
//AuxiliaryFunctions.overwriteDoubleArray(this.SS, other.SS);
assert (LS.length == other.LS.length);
System.a... | [
"protected",
"void",
"overwriteOldCluster",
"(",
"ClusKernel",
"other",
")",
"{",
"this",
".",
"totalN",
"=",
"other",
".",
"totalN",
";",
"this",
".",
"N",
"=",
"other",
".",
"N",
";",
"//AuxiliaryFunctions.overwriteDoubleArray(this.LS, other.LS);",
"//AuxiliaryFun... | Overwrites the LS, SS and weightedN in this cluster to the values of the
given cluster but adds N and classCount of the given cluster to this one.
This function is useful when the weight of an entry becomes to small, and
we want to forget the information of the old points.
@param other The cluster that should overwrite... | [
"Overwrites",
"the",
"LS",
"SS",
"and",
"weightedN",
"in",
"this",
"cluster",
"to",
"the",
"values",
"of",
"the",
"given",
"cluster",
"but",
"adds",
"N",
"and",
"classCount",
"of",
"the",
"given",
"cluster",
"to",
"this",
"one",
".",
"This",
"function",
... | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/clustree/ClusKernel.java#L190-L199 |
29,045 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/SAMkNN.java | SAMkNN.getVotesForInstance | @Override
public double[] getVotesForInstance(Instance inst) {
double vSTM[];
double vLTM[];
double vCM[];
double v[];
double distancesSTM[];
double distancesLTM[];
int predClassSTM = 0;
int predClassLTM = 0;
int predClassCM = 0;
try {
if (this.stm.numInstances()>0) {
d... | java | @Override
public double[] getVotesForInstance(Instance inst) {
double vSTM[];
double vLTM[];
double vCM[];
double v[];
double distancesSTM[];
double distancesLTM[];
int predClassSTM = 0;
int predClassLTM = 0;
int predClassCM = 0;
try {
if (this.stm.numInstances()>0) {
d... | [
"@",
"Override",
"public",
"double",
"[",
"]",
"getVotesForInstance",
"(",
"Instance",
"inst",
")",
"{",
"double",
"vSTM",
"[",
"]",
";",
"double",
"vLTM",
"[",
"]",
";",
"double",
"vCM",
"[",
"]",
";",
"double",
"v",
"[",
"]",
";",
"double",
"distan... | Predicts the label of a given sample by using the STM, LTM and the CM. | [
"Predicts",
"the",
"label",
"of",
"a",
"given",
"sample",
"by",
"using",
"the",
"STM",
"LTM",
"and",
"the",
"CM",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/SAMkNN.java#L178-L226 |
29,046 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/SAMkNN.java | SAMkNN.clusterDown | private void clusterDown(){
int classIndex = this.ltm.classIndex();
for (int c = 0; c <= this.maxClassValue; c++){
List<double[]> classSamples = new ArrayList<>();
for (int i = this.ltm.numInstances()-1; i >-1 ; i--) {
if (this.ltm.get(i).classValue() == c) {
classSamples.add(this.ltm.get(i).toDouble... | java | private void clusterDown(){
int classIndex = this.ltm.classIndex();
for (int c = 0; c <= this.maxClassValue; c++){
List<double[]> classSamples = new ArrayList<>();
for (int i = this.ltm.numInstances()-1; i >-1 ; i--) {
if (this.ltm.get(i).classValue() == c) {
classSamples.add(this.ltm.get(i).toDouble... | [
"private",
"void",
"clusterDown",
"(",
")",
"{",
"int",
"classIndex",
"=",
"this",
".",
"ltm",
".",
"classIndex",
"(",
")",
";",
"for",
"(",
"int",
"c",
"=",
"0",
";",
"c",
"<=",
"this",
".",
"maxClassValue",
";",
"c",
"++",
")",
"{",
"List",
"<"... | Performs classwise kMeans++ clustering for given samples with corresponding labels. The number of samples is halved per class. | [
"Performs",
"classwise",
"kMeans",
"++",
"clustering",
"for",
"given",
"samples",
"with",
"corresponding",
"labels",
".",
"The",
"number",
"of",
"samples",
"is",
"halved",
"per",
"class",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/SAMkNN.java#L260-L299 |
29,047 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/SAMkNN.java | SAMkNN.memorySizeCheck | private void memorySizeCheck(){
if (this.stm.numInstances() + this.ltm.numInstances() > this.maxSTMSize + this.maxLTMSize){
if (this.ltm.numInstances() > this.maxLTMSize){
this.clusterDown();
}else{ //shift values from STM directly to LTM since STM is full
int numShifts = this.maxLTMSize - this.ltm.numI... | java | private void memorySizeCheck(){
if (this.stm.numInstances() + this.ltm.numInstances() > this.maxSTMSize + this.maxLTMSize){
if (this.ltm.numInstances() > this.maxLTMSize){
this.clusterDown();
}else{ //shift values from STM directly to LTM since STM is full
int numShifts = this.maxLTMSize - this.ltm.numI... | [
"private",
"void",
"memorySizeCheck",
"(",
")",
"{",
"if",
"(",
"this",
".",
"stm",
".",
"numInstances",
"(",
")",
"+",
"this",
".",
"ltm",
".",
"numInstances",
"(",
")",
">",
"this",
".",
"maxSTMSize",
"+",
"this",
".",
"maxLTMSize",
")",
"{",
"if",... | Makes sure that the STM and LTM combined doe not surpass the maximum size. | [
"Makes",
"sure",
"that",
"the",
"STM",
"and",
"LTM",
"combined",
"doe",
"not",
"surpass",
"the",
"maximum",
"size",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/SAMkNN.java#L304-L326 |
29,048 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/SAMkNN.java | SAMkNN.clean | private void clean(Instances cleanAgainst, Instances toClean, boolean onlyLast) {
if (cleanAgainst.numInstances() > this.kOption.getValue() && toClean.numInstances() > 0){
if (onlyLast){
cleanSingle(cleanAgainst, (cleanAgainst.numInstances()-1), toClean);
}else{
for (int i=0; i < cleanAgainst.numInstanc... | java | private void clean(Instances cleanAgainst, Instances toClean, boolean onlyLast) {
if (cleanAgainst.numInstances() > this.kOption.getValue() && toClean.numInstances() > 0){
if (onlyLast){
cleanSingle(cleanAgainst, (cleanAgainst.numInstances()-1), toClean);
}else{
for (int i=0; i < cleanAgainst.numInstanc... | [
"private",
"void",
"clean",
"(",
"Instances",
"cleanAgainst",
",",
"Instances",
"toClean",
",",
"boolean",
"onlyLast",
")",
"{",
"if",
"(",
"cleanAgainst",
".",
"numInstances",
"(",
")",
">",
"this",
".",
"kOption",
".",
"getValue",
"(",
")",
"&&",
"toClea... | Removes distance-based all instances from the input samples that contradict those in the STM. | [
"Removes",
"distance",
"-",
"based",
"all",
"instances",
"from",
"the",
"input",
"samples",
"that",
"contradict",
"those",
"in",
"the",
"STM",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/SAMkNN.java#L359-L369 |
29,049 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/SAMkNN.java | SAMkNN.getDistanceWeightedVotes | private double [] getDistanceWeightedVotes(double distances[], int[] nnIndices, Instances instances){
double v[] = new double[this.maxClassValue +1];
for (int nnIdx : nnIndices) {
v[(int)instances.instance(nnIdx).classValue()] += 1./Math.max(distances[nnIdx], 0.000000001);
}
return v;
... | java | private double [] getDistanceWeightedVotes(double distances[], int[] nnIndices, Instances instances){
double v[] = new double[this.maxClassValue +1];
for (int nnIdx : nnIndices) {
v[(int)instances.instance(nnIdx).classValue()] += 1./Math.max(distances[nnIdx], 0.000000001);
}
return v;
... | [
"private",
"double",
"[",
"]",
"getDistanceWeightedVotes",
"(",
"double",
"distances",
"[",
"]",
",",
"int",
"[",
"]",
"nnIndices",
",",
"Instances",
"instances",
")",
"{",
"double",
"v",
"[",
"]",
"=",
"new",
"double",
"[",
"this",
".",
"maxClassValue",
... | Returns the distance weighted votes. | [
"Returns",
"the",
"distance",
"weighted",
"votes",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/SAMkNN.java#L373-L380 |
29,050 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/SAMkNN.java | SAMkNN.getClassFromVotes | private int getClassFromVotes(double votes[]){
double maxVote = -1;
int maxVoteClass = -1;
for (int i = 0; i < votes.length; i++){
if (votes[i] > maxVote){
maxVote = votes[i];
maxVoteClass = i;
}
}
return maxVoteClass;
} | java | private int getClassFromVotes(double votes[]){
double maxVote = -1;
int maxVoteClass = -1;
for (int i = 0; i < votes.length; i++){
if (votes[i] > maxVote){
maxVote = votes[i];
maxVoteClass = i;
}
}
return maxVoteClass;
} | [
"private",
"int",
"getClassFromVotes",
"(",
"double",
"votes",
"[",
"]",
")",
"{",
"double",
"maxVote",
"=",
"-",
"1",
";",
"int",
"maxVoteClass",
"=",
"-",
"1",
";",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"votes",
".",
"length",
";",
"... | Returns the class with maximum vote. | [
"Returns",
"the",
"class",
"with",
"maximum",
"vote",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/SAMkNN.java#L408-L418 |
29,051 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/SAMkNN.java | SAMkNN.getDistance | private double getDistance(Instance sample, Instance sample2)
{
double sum=0;
for (int i=0; i<sample.numInputAttributes(); i++)
{
double diff = sample.valueInputAttribute(i)-sample2.valueInputAttribute(i);
sum += diff*diff;
}
return Math.sqrt(sum);
... | java | private double getDistance(Instance sample, Instance sample2)
{
double sum=0;
for (int i=0; i<sample.numInputAttributes(); i++)
{
double diff = sample.valueInputAttribute(i)-sample2.valueInputAttribute(i);
sum += diff*diff;
}
return Math.sqrt(sum);
... | [
"private",
"double",
"getDistance",
"(",
"Instance",
"sample",
",",
"Instance",
"sample2",
")",
"{",
"double",
"sum",
"=",
"0",
";",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"sample",
".",
"numInputAttributes",
"(",
")",
";",
"i",
"++",
")",
... | Returns the Euclidean distance. | [
"Returns",
"the",
"Euclidean",
"distance",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/SAMkNN.java#L429-L438 |
29,052 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/SAMkNN.java | SAMkNN.get1ToNDistances | private double[] get1ToNDistances(Instance sample, Instances samples){
double distances[] = new double[samples.numInstances()];
for (int i=0; i<samples.numInstances(); i++){
distances[i] = this.getDistance(sample, samples.get(i));
}
return distances;
} | java | private double[] get1ToNDistances(Instance sample, Instances samples){
double distances[] = new double[samples.numInstances()];
for (int i=0; i<samples.numInstances(); i++){
distances[i] = this.getDistance(sample, samples.get(i));
}
return distances;
} | [
"private",
"double",
"[",
"]",
"get1ToNDistances",
"(",
"Instance",
"sample",
",",
"Instances",
"samples",
")",
"{",
"double",
"distances",
"[",
"]",
"=",
"new",
"double",
"[",
"samples",
".",
"numInstances",
"(",
")",
"]",
";",
"for",
"(",
"int",
"i",
... | Returns the Euclidean distance between one sample and a collection of samples in an 1D-array. | [
"Returns",
"the",
"Euclidean",
"distance",
"between",
"one",
"sample",
"and",
"a",
"collection",
"of",
"samples",
"in",
"an",
"1D",
"-",
"array",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/SAMkNN.java#L443-L449 |
29,053 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/SAMkNN.java | SAMkNN.adaptHistories | private void adaptHistories(int numberOfDeletions){
for (int i = 0; i < numberOfDeletions; i++){
SortedSet<Integer> keys = new TreeSet<>(this.predictionHistories.keySet());
this.predictionHistories.remove(keys.first());
keys = new TreeSet<>(this.predictionHistories.keySet());
for (Integer key : keys){
... | java | private void adaptHistories(int numberOfDeletions){
for (int i = 0; i < numberOfDeletions; i++){
SortedSet<Integer> keys = new TreeSet<>(this.predictionHistories.keySet());
this.predictionHistories.remove(keys.first());
keys = new TreeSet<>(this.predictionHistories.keySet());
for (Integer key : keys){
... | [
"private",
"void",
"adaptHistories",
"(",
"int",
"numberOfDeletions",
")",
"{",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"numberOfDeletions",
";",
"i",
"++",
")",
"{",
"SortedSet",
"<",
"Integer",
">",
"keys",
"=",
"new",
"TreeSet",
"<>",
"(",
... | Removes predictions of the largest window size and shifts the remaining ones accordingly. | [
"Removes",
"predictions",
"of",
"the",
"largest",
"window",
"size",
"and",
"shifts",
"the",
"remaining",
"ones",
"accordingly",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/SAMkNN.java#L483-L493 |
29,054 | Waikato/moa | moa/src/main/java/moa/classifiers/lazy/SAMkNN.java | SAMkNN.getHistoryErrorRate | private double getHistoryErrorRate(List<Integer> predHistory){
double sumCorrect = 0;
for (Integer e : predHistory) {
sumCorrect += e;
}
return 1. - (sumCorrect / predHistory.size());
} | java | private double getHistoryErrorRate(List<Integer> predHistory){
double sumCorrect = 0;
for (Integer e : predHistory) {
sumCorrect += e;
}
return 1. - (sumCorrect / predHistory.size());
} | [
"private",
"double",
"getHistoryErrorRate",
"(",
"List",
"<",
"Integer",
">",
"predHistory",
")",
"{",
"double",
"sumCorrect",
"=",
"0",
";",
"for",
"(",
"Integer",
"e",
":",
"predHistory",
")",
"{",
"sumCorrect",
"+=",
"e",
";",
"}",
"return",
"1.",
"-"... | Calculates the achieved error rate of a history. | [
"Calculates",
"the",
"achieved",
"error",
"rate",
"of",
"a",
"history",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/lazy/SAMkNN.java#L558-L564 |
29,055 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/Metric.java | Metric.distanceSquared | public static double distanceSquared(double[] pointA) {
double distance = 0.0;
for (int i = 0; i < pointA.length; i++) {
distance += pointA[i] * pointA[i];
}
return distance;
} | java | public static double distanceSquared(double[] pointA) {
double distance = 0.0;
for (int i = 0; i < pointA.length; i++) {
distance += pointA[i] * pointA[i];
}
return distance;
} | [
"public",
"static",
"double",
"distanceSquared",
"(",
"double",
"[",
"]",
"pointA",
")",
"{",
"double",
"distance",
"=",
"0.0",
";",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"pointA",
".",
"length",
";",
"i",
"++",
")",
"{",
"distance",
"+=... | Calculates the squared Euclidean length of a point.
@param pointA
point
@return the squared Euclidean length | [
"Calculates",
"the",
"squared",
"Euclidean",
"length",
"of",
"a",
"point",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/Metric.java#L35-L41 |
29,056 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/Metric.java | Metric.distanceSquared | public static double distanceSquared(double[] pointA, double[] pointB,
int offsetB) {
assert (pointA.length == pointB.length + offsetB);
double distance = 0.0;
for (int i = 0; i < pointA.length; i++) {
double d = pointA[i] - pointB[i + offsetB];
distance += d * d;
}
return distance;
} | java | public static double distanceSquared(double[] pointA, double[] pointB,
int offsetB) {
assert (pointA.length == pointB.length + offsetB);
double distance = 0.0;
for (int i = 0; i < pointA.length; i++) {
double d = pointA[i] - pointB[i + offsetB];
distance += d * d;
}
return distance;
} | [
"public",
"static",
"double",
"distanceSquared",
"(",
"double",
"[",
"]",
"pointA",
",",
"double",
"[",
"]",
"pointB",
",",
"int",
"offsetB",
")",
"{",
"assert",
"(",
"pointA",
".",
"length",
"==",
"pointB",
".",
"length",
"+",
"offsetB",
")",
";",
"do... | Calculates the squared Euclidean distance of two points. Starts at dimension
offset + 1 of pointB.
@param pointA
first point
@param pointB
second point
@param offsetB
start dimension - 1 of pointB
@return the squared Euclidean distance | [
"Calculates",
"the",
"squared",
"Euclidean",
"distance",
"of",
"two",
"points",
".",
"Starts",
"at",
"dimension",
"offset",
"+",
"1",
"of",
"pointB",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/Metric.java#L66-L75 |
29,057 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/Metric.java | Metric.distance | public static double distance(double[] pointA, double[] pointB, int offsetB) {
return Math.sqrt(distanceSquared(pointA, pointB, offsetB));
} | java | public static double distance(double[] pointA, double[] pointB, int offsetB) {
return Math.sqrt(distanceSquared(pointA, pointB, offsetB));
} | [
"public",
"static",
"double",
"distance",
"(",
"double",
"[",
"]",
"pointA",
",",
"double",
"[",
"]",
"pointB",
",",
"int",
"offsetB",
")",
"{",
"return",
"Math",
".",
"sqrt",
"(",
"distanceSquared",
"(",
"pointA",
",",
"pointB",
",",
"offsetB",
")",
"... | Calculates the Euclidean distance of two points. Starts at dimension offset
+ 1 of pointB.
@param pointA
first point
@param pointB
second point
@param offsetB
start dimension - 1 of pointB
@return the Euclidean distance | [
"Calculates",
"the",
"Euclidean",
"distance",
"of",
"two",
"points",
".",
"Starts",
"at",
"dimension",
"offset",
"+",
"1",
"of",
"pointB",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/Metric.java#L89-L91 |
29,058 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/Metric.java | Metric.distanceWithDivisionSquared | public static double distanceWithDivisionSquared(double[] pointA, double dA) {
double distance = 0.0;
for (int i = 0; i < pointA.length; i++) {
double d = pointA[i] / dA;
distance += d * d;
}
return distance;
} | java | public static double distanceWithDivisionSquared(double[] pointA, double dA) {
double distance = 0.0;
for (int i = 0; i < pointA.length; i++) {
double d = pointA[i] / dA;
distance += d * d;
}
return distance;
} | [
"public",
"static",
"double",
"distanceWithDivisionSquared",
"(",
"double",
"[",
"]",
"pointA",
",",
"double",
"dA",
")",
"{",
"double",
"distance",
"=",
"0.0",
";",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"pointA",
".",
"length",
";",
"i",
... | Calculates the squared Euclidean length of a point divided by a scalar.
@param pointA
point
@param dA
scalar
@return the squared Euclidean length | [
"Calculates",
"the",
"squared",
"Euclidean",
"length",
"of",
"a",
"point",
"divided",
"by",
"a",
"scalar",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/Metric.java#L134-L141 |
29,059 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/Metric.java | Metric.distanceWithDivision | public static double distanceWithDivision(double[] pointA, double dA,
double[] pointB) {
return Math.sqrt(distanceWithDivisionSquared(pointA, dA, pointB));
} | java | public static double distanceWithDivision(double[] pointA, double dA,
double[] pointB) {
return Math.sqrt(distanceWithDivisionSquared(pointA, dA, pointB));
} | [
"public",
"static",
"double",
"distanceWithDivision",
"(",
"double",
"[",
"]",
"pointA",
",",
"double",
"dA",
",",
"double",
"[",
"]",
"pointB",
")",
"{",
"return",
"Math",
".",
"sqrt",
"(",
"distanceWithDivisionSquared",
"(",
"pointA",
",",
"dA",
",",
"po... | Calculates the Euclidean distance of the first point divided by a scalar and
another second point.
@param pointA
first point
@param dA
scalar
@param pointB
second point
@return the Euclidean distance | [
"Calculates",
"the",
"Euclidean",
"distance",
"of",
"the",
"first",
"point",
"divided",
"by",
"a",
"scalar",
"and",
"another",
"second",
"point",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/Metric.java#L191-L194 |
29,060 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/Metric.java | Metric.dotProduct | public static double dotProduct(double[] pointA) {
double product = 0.0;
for (int i = 0; i < pointA.length; i++) {
product += pointA[i] * pointA[i];
}
return product;
} | java | public static double dotProduct(double[] pointA) {
double product = 0.0;
for (int i = 0; i < pointA.length; i++) {
product += pointA[i] * pointA[i];
}
return product;
} | [
"public",
"static",
"double",
"dotProduct",
"(",
"double",
"[",
"]",
"pointA",
")",
"{",
"double",
"product",
"=",
"0.0",
";",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"pointA",
".",
"length",
";",
"i",
"++",
")",
"{",
"product",
"+=",
"p... | Calculates the dot product of the point with itself.
@param pointA
point
@return the dot product | [
"Calculates",
"the",
"dot",
"product",
"of",
"the",
"point",
"with",
"itself",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/Metric.java#L247-L253 |
29,061 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/Metric.java | Metric.dotProductWithAddition | public static double dotProductWithAddition(double[] pointA1,
double[] pointA2, double[] pointB) {
assert (pointA1.length == pointA2.length && pointA1.length == pointB.length);
double product = 0.0;
for (int i = 0; i < pointA1.length; i++) {
product += (pointA1[i] + pointA2[i]) * pointB[i];
}
return pro... | java | public static double dotProductWithAddition(double[] pointA1,
double[] pointA2, double[] pointB) {
assert (pointA1.length == pointA2.length && pointA1.length == pointB.length);
double product = 0.0;
for (int i = 0; i < pointA1.length; i++) {
product += (pointA1[i] + pointA2[i]) * pointB[i];
}
return pro... | [
"public",
"static",
"double",
"dotProductWithAddition",
"(",
"double",
"[",
"]",
"pointA1",
",",
"double",
"[",
"]",
"pointA2",
",",
"double",
"[",
"]",
"pointB",
")",
"{",
"assert",
"(",
"pointA1",
".",
"length",
"==",
"pointA2",
".",
"length",
"&&",
"p... | Calculates the dot product of the addition of the first and the second
point with the third point.
@param pointA1
first point
@param pointA2
second point
@param pointB
third point
@return the dot product | [
"Calculates",
"the",
"dot",
"product",
"of",
"the",
"addition",
"of",
"the",
"first",
"and",
"the",
"second",
"point",
"with",
"the",
"third",
"point",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/Metric.java#L285-L293 |
29,062 | Waikato/moa | moa/src/main/java/moa/clusterers/kmeanspm/Metric.java | Metric.dotProductWithAddition | public static double dotProductWithAddition(double[] pointA1,
double[] pointA2, double[] pointB1, double[] pointB2) {
assert (pointA1.length == pointA2.length
&& pointB1.length == pointB2.length && pointA1.length == pointB1.length);
double product = 0.0;
for (int i = 0; i < pointA1.length; i++) {
produc... | java | public static double dotProductWithAddition(double[] pointA1,
double[] pointA2, double[] pointB1, double[] pointB2) {
assert (pointA1.length == pointA2.length
&& pointB1.length == pointB2.length && pointA1.length == pointB1.length);
double product = 0.0;
for (int i = 0; i < pointA1.length; i++) {
produc... | [
"public",
"static",
"double",
"dotProductWithAddition",
"(",
"double",
"[",
"]",
"pointA1",
",",
"double",
"[",
"]",
"pointA2",
",",
"double",
"[",
"]",
"pointB1",
",",
"double",
"[",
"]",
"pointB2",
")",
"{",
"assert",
"(",
"pointA1",
".",
"length",
"==... | Calculates the dot product of the addition of the first and the second
point with the addition of the third and the fourth point.
@param pointA1
first point
@param pointA2
second point
@param pointB1
third point
@param pointB2
fourth point
@return the dot product | [
"Calculates",
"the",
"dot",
"product",
"of",
"the",
"addition",
"of",
"the",
"first",
"and",
"the",
"second",
"point",
"with",
"the",
"addition",
"of",
"the",
"third",
"and",
"the",
"fourth",
"point",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/kmeanspm/Metric.java#L309-L318 |
29,063 | Waikato/moa | moa/src/main/java/com/yahoo/labs/samoa/instances/WekaToSamoaInstanceConverter.java | WekaToSamoaInstanceConverter.samoaInstance | public Instance samoaInstance(weka.core.Instance inst) {
Instance samoaInstance;
if (inst instanceof weka.core.SparseInstance) {
double[] attributeValues = new double[inst.numValues()];
int[] indexValues = new int[inst.numValues()];
for (int i = 0; i < inst.numValues(... | java | public Instance samoaInstance(weka.core.Instance inst) {
Instance samoaInstance;
if (inst instanceof weka.core.SparseInstance) {
double[] attributeValues = new double[inst.numValues()];
int[] indexValues = new int[inst.numValues()];
for (int i = 0; i < inst.numValues(... | [
"public",
"Instance",
"samoaInstance",
"(",
"weka",
".",
"core",
".",
"Instance",
"inst",
")",
"{",
"Instance",
"samoaInstance",
";",
"if",
"(",
"inst",
"instanceof",
"weka",
".",
"core",
".",
"SparseInstance",
")",
"{",
"double",
"[",
"]",
"attributeValues"... | Samoa instance from weka instance.
@param inst the inst
@return the instance | [
"Samoa",
"instance",
"from",
"weka",
"instance",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/com/yahoo/labs/samoa/instances/WekaToSamoaInstanceConverter.java#L37-L64 |
29,064 | Waikato/moa | moa/src/main/java/com/yahoo/labs/samoa/instances/WekaToSamoaInstanceConverter.java | WekaToSamoaInstanceConverter.samoaInstances | public Instances samoaInstances(weka.core.Instances instances) {
Instances samoaInstances = samoaInstancesInformation(instances);
//We assume that we have only one samoaInstanceInformation for WekaToSamoaInstanceConverter
this.samoaInstanceInformation = samoaInstances;
for (int i = 0; i ... | java | public Instances samoaInstances(weka.core.Instances instances) {
Instances samoaInstances = samoaInstancesInformation(instances);
//We assume that we have only one samoaInstanceInformation for WekaToSamoaInstanceConverter
this.samoaInstanceInformation = samoaInstances;
for (int i = 0; i ... | [
"public",
"Instances",
"samoaInstances",
"(",
"weka",
".",
"core",
".",
"Instances",
"instances",
")",
"{",
"Instances",
"samoaInstances",
"=",
"samoaInstancesInformation",
"(",
"instances",
")",
";",
"//We assume that we have only one samoaInstanceInformation for WekaToSamoa... | Samoa instances from weka instances.
@param instances the instances
@return the instances | [
"Samoa",
"instances",
"from",
"weka",
"instances",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/com/yahoo/labs/samoa/instances/WekaToSamoaInstanceConverter.java#L72-L80 |
29,065 | Waikato/moa | moa/src/main/java/com/yahoo/labs/samoa/instances/WekaToSamoaInstanceConverter.java | WekaToSamoaInstanceConverter.samoaInstancesInformation | public Instances samoaInstancesInformation(weka.core.Instances instances) {
Instances samoaInstances;
List<Attribute> attInfo = new ArrayList<Attribute>();
for (int i = 0; i < instances.numAttributes(); i++) {
attInfo.add(samoaAttribute(i, instances.attribute(i)));
}
... | java | public Instances samoaInstancesInformation(weka.core.Instances instances) {
Instances samoaInstances;
List<Attribute> attInfo = new ArrayList<Attribute>();
for (int i = 0; i < instances.numAttributes(); i++) {
attInfo.add(samoaAttribute(i, instances.attribute(i)));
}
... | [
"public",
"Instances",
"samoaInstancesInformation",
"(",
"weka",
".",
"core",
".",
"Instances",
"instances",
")",
"{",
"Instances",
"samoaInstances",
";",
"List",
"<",
"Attribute",
">",
"attInfo",
"=",
"new",
"ArrayList",
"<",
"Attribute",
">",
"(",
")",
";",
... | Samoa instances information.
@param instances the instances
@return the instances | [
"Samoa",
"instances",
"information",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/com/yahoo/labs/samoa/instances/WekaToSamoaInstanceConverter.java#L88-L101 |
29,066 | Waikato/moa | moa/src/main/java/com/yahoo/labs/samoa/instances/WekaToSamoaInstanceConverter.java | WekaToSamoaInstanceConverter.samoaAttribute | protected Attribute samoaAttribute(int index, weka.core.Attribute attribute) {
Attribute samoaAttribute;
if (attribute.isNominal()) {
Enumeration enu = attribute.enumerateValues();
List<String> attributeValues = new ArrayList<String>();
while (enu.hasMoreElements()) {... | java | protected Attribute samoaAttribute(int index, weka.core.Attribute attribute) {
Attribute samoaAttribute;
if (attribute.isNominal()) {
Enumeration enu = attribute.enumerateValues();
List<String> attributeValues = new ArrayList<String>();
while (enu.hasMoreElements()) {... | [
"protected",
"Attribute",
"samoaAttribute",
"(",
"int",
"index",
",",
"weka",
".",
"core",
".",
"Attribute",
"attribute",
")",
"{",
"Attribute",
"samoaAttribute",
";",
"if",
"(",
"attribute",
".",
"isNominal",
"(",
")",
")",
"{",
"Enumeration",
"enu",
"=",
... | Get Samoa attribute from a weka attribute.
@param index the index
@param attribute the attribute
@return the attribute | [
"Get",
"Samoa",
"attribute",
"from",
"a",
"weka",
"attribute",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/com/yahoo/labs/samoa/instances/WekaToSamoaInstanceConverter.java#L111-L124 |
29,067 | Waikato/moa | moa/src/main/java/moa/gui/experimentertab/ImagePanel.java | ImagePanel.doSaveAs | @Override
public void doSaveAs() throws IOException {
JFileChooser fileChooser = new JFileChooser();
ExtensionFileFilter filterPNG = new ExtensionFileFilter("PNG Image Files", ".png");
fileChooser.addChoosableFileFilter(filterPNG);
ExtensionFileFilter filterJPG = new ExtensionFileF... | java | @Override
public void doSaveAs() throws IOException {
JFileChooser fileChooser = new JFileChooser();
ExtensionFileFilter filterPNG = new ExtensionFileFilter("PNG Image Files", ".png");
fileChooser.addChoosableFileFilter(filterPNG);
ExtensionFileFilter filterJPG = new ExtensionFileF... | [
"@",
"Override",
"public",
"void",
"doSaveAs",
"(",
")",
"throws",
"IOException",
"{",
"JFileChooser",
"fileChooser",
"=",
"new",
"JFileChooser",
"(",
")",
";",
"ExtensionFileFilter",
"filterPNG",
"=",
"new",
"ExtensionFileFilter",
"(",
"\"PNG Image Files\"",
",",
... | Method for save the images.
@throws IOException | [
"Method",
"for",
"save",
"the",
"images",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/experimentertab/ImagePanel.java#L57-L91 |
29,068 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.round | protected BigDecimal round(double val){
BigDecimal value = new BigDecimal(val);
if(val!=0.0){
value = value.setScale(3, BigDecimal.ROUND_DOWN);
}
return value;
} | java | protected BigDecimal round(double val){
BigDecimal value = new BigDecimal(val);
if(val!=0.0){
value = value.setScale(3, BigDecimal.ROUND_DOWN);
}
return value;
} | [
"protected",
"BigDecimal",
"round",
"(",
"double",
"val",
")",
"{",
"BigDecimal",
"value",
"=",
"new",
"BigDecimal",
"(",
"val",
")",
";",
"if",
"(",
"val",
"!=",
"0.0",
")",
"{",
"value",
"=",
"value",
".",
"setScale",
"(",
"3",
",",
"BigDecimal",
"... | Round an number | [
"Round",
"an",
"number"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L551-L557 |
29,069 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.initializeRuleStatistics | public void initializeRuleStatistics(RuleClassification rl, Predicates pred, Instance inst) {
rl.predicateSet.add(pred);
rl.obserClassDistrib=new DoubleVector();
rl.observers=new AutoExpandVector<AttributeClassObserver>();
rl.observersGauss=new AutoExpandVector<AttributeClassObserver>();
rl.instancesSeen = 0;... | java | public void initializeRuleStatistics(RuleClassification rl, Predicates pred, Instance inst) {
rl.predicateSet.add(pred);
rl.obserClassDistrib=new DoubleVector();
rl.observers=new AutoExpandVector<AttributeClassObserver>();
rl.observersGauss=new AutoExpandVector<AttributeClassObserver>();
rl.instancesSeen = 0;... | [
"public",
"void",
"initializeRuleStatistics",
"(",
"RuleClassification",
"rl",
",",
"Predicates",
"pred",
",",
"Instance",
"inst",
")",
"{",
"rl",
".",
"predicateSet",
".",
"add",
"(",
"pred",
")",
";",
"rl",
".",
"obserClassDistrib",
"=",
"new",
"DoubleVector... | This function initializes the statistics of a rule | [
"This",
"function",
"initializes",
"the",
"statistics",
"of",
"a",
"rule"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L561-L572 |
29,070 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.updateRuleAttribStatistics | public void updateRuleAttribStatistics(Instance inst, RuleClassification rl, int ruleIndex){
rl.instancesSeen++;
if(rl.squaredAttributeStatisticsSupervised.size() == 0 && rl.attributeStatisticsSupervised.size() == 0){
for (int s = 0; s < inst.numAttributes() -1; s++) {
ArrayList<Double> temp1 = new ArrayLis... | java | public void updateRuleAttribStatistics(Instance inst, RuleClassification rl, int ruleIndex){
rl.instancesSeen++;
if(rl.squaredAttributeStatisticsSupervised.size() == 0 && rl.attributeStatisticsSupervised.size() == 0){
for (int s = 0; s < inst.numAttributes() -1; s++) {
ArrayList<Double> temp1 = new ArrayLis... | [
"public",
"void",
"updateRuleAttribStatistics",
"(",
"Instance",
"inst",
",",
"RuleClassification",
"rl",
",",
"int",
"ruleIndex",
")",
"{",
"rl",
".",
"instancesSeen",
"++",
";",
"if",
"(",
"rl",
".",
"squaredAttributeStatisticsSupervised",
".",
"size",
"(",
")... | Update rule statistics | [
"Update",
"rule",
"statistics"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L575-L607 |
29,071 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.createRule | public void createRule(Instance inst) {
int remainder = (int)Double.MAX_VALUE;
int numInstanciaObservers = (int)this.observedClassDistribution.sumOfValues();
if (numInstanciaObservers != 0 && this.gracePeriodOption.getValue() != 0) {
remainder = (numInstanciaObservers) % (this.gracePeriodOption.getValue());
... | java | public void createRule(Instance inst) {
int remainder = (int)Double.MAX_VALUE;
int numInstanciaObservers = (int)this.observedClassDistribution.sumOfValues();
if (numInstanciaObservers != 0 && this.gracePeriodOption.getValue() != 0) {
remainder = (numInstanciaObservers) % (this.gracePeriodOption.getValue());
... | [
"public",
"void",
"createRule",
"(",
"Instance",
"inst",
")",
"{",
"int",
"remainder",
"=",
"(",
"int",
")",
"Double",
".",
"MAX_VALUE",
";",
"int",
"numInstanciaObservers",
"=",
"(",
"int",
")",
"this",
".",
"observedClassDistribution",
".",
"sumOfValues",
... | This function creates a rule | [
"This",
"function",
"creates",
"a",
"rule"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L775-L809 |
29,072 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.theBestAttributes | public void theBestAttributes(Instance instance,
AutoExpandVector<AttributeClassObserver> observersParameter) {
for(int z = 0; z < instance.numAttributes() - 1; z++){
if(!instance.isMissing(z)){
int instAttIndex = modelAttIndexToInstanceAttIndex(z, instance);
ArrayList<Double> attribBest = new ArrayList<... | java | public void theBestAttributes(Instance instance,
AutoExpandVector<AttributeClassObserver> observersParameter) {
for(int z = 0; z < instance.numAttributes() - 1; z++){
if(!instance.isMissing(z)){
int instAttIndex = modelAttIndexToInstanceAttIndex(z, instance);
ArrayList<Double> attribBest = new ArrayList<... | [
"public",
"void",
"theBestAttributes",
"(",
"Instance",
"instance",
",",
"AutoExpandVector",
"<",
"AttributeClassObserver",
">",
"observersParameter",
")",
"{",
"for",
"(",
"int",
"z",
"=",
"0",
";",
"z",
"<",
"instance",
".",
"numAttributes",
"(",
")",
"-",
... | This function gives the best value of entropy for each attribute | [
"This",
"function",
"gives",
"the",
"best",
"value",
"of",
"entropy",
"for",
"each",
"attribute"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L914-L944 |
29,073 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.mainFindBestValEntropy | public void mainFindBestValEntropy(Node root) {
if (root != null) {
DoubleVector parentClassCL = new DoubleVector();
DoubleVector classCountL = root.classCountsLeft; //class count left
DoubleVector classCountR = root.classCountsRight; //class count left
double numInst = root.classCountsLeft.sumOfValues() ... | java | public void mainFindBestValEntropy(Node root) {
if (root != null) {
DoubleVector parentClassCL = new DoubleVector();
DoubleVector classCountL = root.classCountsLeft; //class count left
DoubleVector classCountR = root.classCountsRight; //class count left
double numInst = root.classCountsLeft.sumOfValues() ... | [
"public",
"void",
"mainFindBestValEntropy",
"(",
"Node",
"root",
")",
"{",
"if",
"(",
"root",
"!=",
"null",
")",
"{",
"DoubleVector",
"parentClassCL",
"=",
"new",
"DoubleVector",
"(",
")",
";",
"DoubleVector",
"classCountL",
"=",
"root",
".",
"classCountsLeft"... | Best value of entropy | [
"Best",
"value",
"of",
"entropy"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L1056-L1073 |
29,074 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.findBestValEntropyNominalAtt | public void findBestValEntropyNominalAtt(AutoExpandVector<DoubleVector> attrib, int attNumValues) {
ArrayList<ArrayList<Double>> distClassValue = new ArrayList<ArrayList<Double>>();
// System.out.print("attrib"+attrib+"\n");
for (int z = 0; z < attrib.size(); z++) {
distClassValue.add(new ArrayList<Double>());... | java | public void findBestValEntropyNominalAtt(AutoExpandVector<DoubleVector> attrib, int attNumValues) {
ArrayList<ArrayList<Double>> distClassValue = new ArrayList<ArrayList<Double>>();
// System.out.print("attrib"+attrib+"\n");
for (int z = 0; z < attrib.size(); z++) {
distClassValue.add(new ArrayList<Double>());... | [
"public",
"void",
"findBestValEntropyNominalAtt",
"(",
"AutoExpandVector",
"<",
"DoubleVector",
">",
"attrib",
",",
"int",
"attNumValues",
")",
"{",
"ArrayList",
"<",
"ArrayList",
"<",
"Double",
">>",
"distClassValue",
"=",
"new",
"ArrayList",
"<",
"ArrayList",
"<... | Find best value of entropy for nominal attributes | [
"Find",
"best",
"value",
"of",
"entropy",
"for",
"nominal",
"attributes"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L1076-L1106 |
29,075 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.checkBestAttrib | public boolean checkBestAttrib(double n,
AutoExpandVector<AttributeClassObserver> observerss, DoubleVector observedClassDistribution){
double h0 = entropy(observedClassDistribution);
boolean isTheBest = false;
double[] entropyValues = getBestSecondBestEntropy(this.saveBestGlobalEntropy);
double bestEntropy ... | java | public boolean checkBestAttrib(double n,
AutoExpandVector<AttributeClassObserver> observerss, DoubleVector observedClassDistribution){
double h0 = entropy(observedClassDistribution);
boolean isTheBest = false;
double[] entropyValues = getBestSecondBestEntropy(this.saveBestGlobalEntropy);
double bestEntropy ... | [
"public",
"boolean",
"checkBestAttrib",
"(",
"double",
"n",
",",
"AutoExpandVector",
"<",
"AttributeClassObserver",
">",
"observerss",
",",
"DoubleVector",
"observedClassDistribution",
")",
"{",
"double",
"h0",
"=",
"entropy",
"(",
"observedClassDistribution",
")",
";... | Check if the best attribute is really the best | [
"Check",
"if",
"the",
"best",
"attribute",
"is",
"really",
"the",
"best"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L1117-L1145 |
29,076 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.getBestSecondBestEntropy | protected double [] getBestSecondBestEntropy(DoubleVector entropy){
double[] entropyValues = new double[2];
double best = Double.MAX_VALUE;
double secondBest = Double.MAX_VALUE;
for (int i = 0; i < entropy.numValues(); i++) {
if (entropy.getValue(i) < best) {
secondBest = best;
best = entropy.getValu... | java | protected double [] getBestSecondBestEntropy(DoubleVector entropy){
double[] entropyValues = new double[2];
double best = Double.MAX_VALUE;
double secondBest = Double.MAX_VALUE;
for (int i = 0; i < entropy.numValues(); i++) {
if (entropy.getValue(i) < best) {
secondBest = best;
best = entropy.getValu... | [
"protected",
"double",
"[",
"]",
"getBestSecondBestEntropy",
"(",
"DoubleVector",
"entropy",
")",
"{",
"double",
"[",
"]",
"entropyValues",
"=",
"new",
"double",
"[",
"2",
"]",
";",
"double",
"best",
"=",
"Double",
".",
"MAX_VALUE",
";",
"double",
"secondBes... | Get best and second best attributes | [
"Get",
"best",
"and",
"second",
"best",
"attributes"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L1148-L1166 |
29,077 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.getRuleMajorityClassIndex | protected double getRuleMajorityClassIndex(RuleClassification r) {
double maxvalue = 0.0;
int posMaxValue = 0;
for (int i = 0; i < r.obserClassDistrib.numValues(); i++) {
if (r.obserClassDistrib.getValue(i) > maxvalue) {
maxvalue = r.obserClassDistrib.getValue(i);
posMaxValue = i;
}
}
return (do... | java | protected double getRuleMajorityClassIndex(RuleClassification r) {
double maxvalue = 0.0;
int posMaxValue = 0;
for (int i = 0; i < r.obserClassDistrib.numValues(); i++) {
if (r.obserClassDistrib.getValue(i) > maxvalue) {
maxvalue = r.obserClassDistrib.getValue(i);
posMaxValue = i;
}
}
return (do... | [
"protected",
"double",
"getRuleMajorityClassIndex",
"(",
"RuleClassification",
"r",
")",
"{",
"double",
"maxvalue",
"=",
"0.0",
";",
"int",
"posMaxValue",
"=",
"0",
";",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"r",
".",
"obserClassDistrib",
".",
... | Get rule majority class index | [
"Get",
"rule",
"majority",
"class",
"index"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L1169-L1179 |
29,078 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.oberversDistribProb | protected double[] oberversDistribProb(Instance inst,
DoubleVector classDistrib) {
double[] votes = new double[this.numClass];
double sum = classDistrib.sumOfValues();
for (int z = 0; z < this.numClass; z++) {
votes[z] = classDistrib.getValue(z) / sum;
}
return votes;
} | java | protected double[] oberversDistribProb(Instance inst,
DoubleVector classDistrib) {
double[] votes = new double[this.numClass];
double sum = classDistrib.sumOfValues();
for (int z = 0; z < this.numClass; z++) {
votes[z] = classDistrib.getValue(z) / sum;
}
return votes;
} | [
"protected",
"double",
"[",
"]",
"oberversDistribProb",
"(",
"Instance",
"inst",
",",
"DoubleVector",
"classDistrib",
")",
"{",
"double",
"[",
"]",
"votes",
"=",
"new",
"double",
"[",
"this",
".",
"numClass",
"]",
";",
"double",
"sum",
"=",
"classDistrib",
... | Get observers class distribution probability | [
"Get",
"observers",
"class",
"distribution",
"probability"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L1182-L1190 |
29,079 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.weightedMax | protected double[] weightedMax(Instance inst) {
int countFired = 0;
boolean fired = false;
double highest = 0.0;
double[] votes = new double[this.numClass];
ArrayList<Double> ruleSetVotes = new ArrayList<Double>();
ArrayList<ArrayList<Double>> majorityProb = new ArrayList<ArrayList<Double>>();
for (int j ... | java | protected double[] weightedMax(Instance inst) {
int countFired = 0;
boolean fired = false;
double highest = 0.0;
double[] votes = new double[this.numClass];
ArrayList<Double> ruleSetVotes = new ArrayList<Double>();
ArrayList<ArrayList<Double>> majorityProb = new ArrayList<ArrayList<Double>>();
for (int j ... | [
"protected",
"double",
"[",
"]",
"weightedMax",
"(",
"Instance",
"inst",
")",
"{",
"int",
"countFired",
"=",
"0",
";",
"boolean",
"fired",
"=",
"false",
";",
"double",
"highest",
"=",
"0.0",
";",
"double",
"[",
"]",
"votes",
"=",
"new",
"double",
"[",
... | Get the votes using weighted Max | [
"Get",
"the",
"votes",
"using",
"weighted",
"Max"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L1219-L1258 |
29,080 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/RuleClassifier.java | RuleClassifier.weightedSum | protected double[] weightedSum(Instance inst) {
boolean fired = false;
int countFired = 0;
double[] votes = new double[this.numClass];
ArrayList<Double> weightSum = new ArrayList<Double>();
ArrayList<ArrayList<Double>> majorityProb = new ArrayList<ArrayList<Double>>();
for (int j = 0; j < this.ruleSet.size(... | java | protected double[] weightedSum(Instance inst) {
boolean fired = false;
int countFired = 0;
double[] votes = new double[this.numClass];
ArrayList<Double> weightSum = new ArrayList<Double>();
ArrayList<ArrayList<Double>> majorityProb = new ArrayList<ArrayList<Double>>();
for (int j = 0; j < this.ruleSet.size(... | [
"protected",
"double",
"[",
"]",
"weightedSum",
"(",
"Instance",
"inst",
")",
"{",
"boolean",
"fired",
"=",
"false",
";",
"int",
"countFired",
"=",
"0",
";",
"double",
"[",
"]",
"votes",
"=",
"new",
"double",
"[",
"this",
".",
"numClass",
"]",
";",
"... | Get the votes using weighted Sum | [
"Get",
"the",
"votes",
"using",
"weighted",
"Sum"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/RuleClassifier.java#L1261-L1296 |
29,081 | Waikato/moa | moa/src/main/java/weka/gui/MOAClassOptionEditor.java | MOAClassOptionEditor.closeDialog | protected void closeDialog() {
if (m_CustomEditor instanceof Container) {
Dialog dlg = PropertyDialog.getParentDialog((Container) m_CustomEditor);
if (dlg != null)
dlg.setVisible(false);
}
} | java | protected void closeDialog() {
if (m_CustomEditor instanceof Container) {
Dialog dlg = PropertyDialog.getParentDialog((Container) m_CustomEditor);
if (dlg != null)
dlg.setVisible(false);
}
} | [
"protected",
"void",
"closeDialog",
"(",
")",
"{",
"if",
"(",
"m_CustomEditor",
"instanceof",
"Container",
")",
"{",
"Dialog",
"dlg",
"=",
"PropertyDialog",
".",
"getParentDialog",
"(",
"(",
"Container",
")",
"m_CustomEditor",
")",
";",
"if",
"(",
"dlg",
"!=... | Closes the dialog. | [
"Closes",
"the",
"dialog",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/weka/gui/MOAClassOptionEditor.java#L65-L71 |
29,082 | Waikato/moa | moa/src/main/java/weka/gui/MOAClassOptionEditor.java | MOAClassOptionEditor.createCustomEditor | protected Component createCustomEditor() {
JPanel panel;
panel = new JPanel(new BorderLayout());
panel.setBorder(BorderFactory.createEmptyBorder(5, 5, 5, 5));
m_EditComponent = (ClassOptionEditComponent) getEditComponent((ClassOption) getValue());
m_EditComponent.addChangeListener(new ChangeListener() {
... | java | protected Component createCustomEditor() {
JPanel panel;
panel = new JPanel(new BorderLayout());
panel.setBorder(BorderFactory.createEmptyBorder(5, 5, 5, 5));
m_EditComponent = (ClassOptionEditComponent) getEditComponent((ClassOption) getValue());
m_EditComponent.addChangeListener(new ChangeListener() {
... | [
"protected",
"Component",
"createCustomEditor",
"(",
")",
"{",
"JPanel",
"panel",
";",
"panel",
"=",
"new",
"JPanel",
"(",
"new",
"BorderLayout",
"(",
")",
")",
";",
"panel",
".",
"setBorder",
"(",
"BorderFactory",
".",
"createEmptyBorder",
"(",
"5",
",",
... | Creates the custom editor.
@return the editor | [
"Creates",
"the",
"custom",
"editor",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/weka/gui/MOAClassOptionEditor.java#L78-L93 |
29,083 | Waikato/moa | moa/src/main/java/weka/gui/MOAClassOptionEditor.java | MOAClassOptionEditor.paintValue | public void paintValue(Graphics gfx, Rectangle box) {
FontMetrics fm;
int vpad;
String val;
fm = gfx.getFontMetrics();
vpad = (box.height - fm.getHeight()) / 2 ;
val = ((ClassOption) getValue()).getValueAsCLIString();
gfx.drawString(val, 2, fm.getHeight() + vpad);
} | java | public void paintValue(Graphics gfx, Rectangle box) {
FontMetrics fm;
int vpad;
String val;
fm = gfx.getFontMetrics();
vpad = (box.height - fm.getHeight()) / 2 ;
val = ((ClassOption) getValue()).getValueAsCLIString();
gfx.drawString(val, 2, fm.getHeight() + vpad);
} | [
"public",
"void",
"paintValue",
"(",
"Graphics",
"gfx",
",",
"Rectangle",
"box",
")",
"{",
"FontMetrics",
"fm",
";",
"int",
"vpad",
";",
"String",
"val",
";",
"fm",
"=",
"gfx",
".",
"getFontMetrics",
"(",
")",
";",
"vpad",
"=",
"(",
"box",
".",
"heig... | Paints a representation of the current Object.
@param gfx the graphics context to use
@param box the area we are allowed to paint into | [
"Paints",
"a",
"representation",
"of",
"the",
"current",
"Object",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/weka/gui/MOAClassOptionEditor.java#L117-L126 |
29,084 | Waikato/moa | moa/src/main/java/moa/classifiers/rules/functions/Perceptron.java | Perceptron.prediction | private double prediction(Instance inst)
{
if(this.initialisePerceptron){
return 0;
}else{
double[] normalizedInstance = normalizedInstance(inst);
double normalizedPrediction = prediction(normalizedInstance);
return denormalizedPrediction(normalizedPrediction);
}
} | java | private double prediction(Instance inst)
{
if(this.initialisePerceptron){
return 0;
}else{
double[] normalizedInstance = normalizedInstance(inst);
double normalizedPrediction = prediction(normalizedInstance);
return denormalizedPrediction(normalizedPrediction);
}
} | [
"private",
"double",
"prediction",
"(",
"Instance",
"inst",
")",
"{",
"if",
"(",
"this",
".",
"initialisePerceptron",
")",
"{",
"return",
"0",
";",
"}",
"else",
"{",
"double",
"[",
"]",
"normalizedInstance",
"=",
"normalizedInstance",
"(",
"inst",
")",
";"... | Output the prediction made by this perceptron on the given instance | [
"Output",
"the",
"prediction",
"made",
"by",
"this",
"perceptron",
"on",
"the",
"given",
"instance"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/rules/functions/Perceptron.java#L231-L240 |
29,085 | Waikato/moa | moa/src/main/java/moa/clusterers/streamkm/BucketManager.java | BucketManager.insertPoint | void insertPoint(Point p){
//check if there is enough space in the first bucket
int cursize = this.buckets[0].cursize;
if(cursize >= this.maxBucketsize) {
//printf("Bucket 0 full \n");
//start spillover process
int curbucket = 0;
int nextbucket = 1;
//check if the next bucket is empty
if(t... | java | void insertPoint(Point p){
//check if there is enough space in the first bucket
int cursize = this.buckets[0].cursize;
if(cursize >= this.maxBucketsize) {
//printf("Bucket 0 full \n");
//start spillover process
int curbucket = 0;
int nextbucket = 1;
//check if the next bucket is empty
if(t... | [
"void",
"insertPoint",
"(",
"Point",
"p",
")",
"{",
"//check if there is enough space in the first bucket",
"int",
"cursize",
"=",
"this",
".",
"buckets",
"[",
"0",
"]",
".",
"cursize",
";",
"if",
"(",
"cursize",
">=",
"this",
".",
"maxBucketsize",
")",
"{",
... | inserts a single point into the bucketmanager | [
"inserts",
"a",
"single",
"point",
"into",
"the",
"bucketmanager"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/streamkm/BucketManager.java#L55-L116 |
29,086 | Waikato/moa | moa/src/main/java/moa/classifiers/meta/AccuracyUpdatedEnsemble.java | AccuracyUpdatedEnsemble.processChunk | protected void processChunk() {
Classifier addedClassifier = null;
double mse_r = this.computeMseR();
// Compute weights
double candidateClassifierWeight = 1.0 / (mse_r + Double.MIN_VALUE);
for (int i = 0; i < this.learners.length; i++) {
this.weights[i][0] = 1.0 / (mse_r + this.computeMse(this.l... | java | protected void processChunk() {
Classifier addedClassifier = null;
double mse_r = this.computeMseR();
// Compute weights
double candidateClassifierWeight = 1.0 / (mse_r + Double.MIN_VALUE);
for (int i = 0; i < this.learners.length; i++) {
this.weights[i][0] = 1.0 / (mse_r + this.computeMse(this.l... | [
"protected",
"void",
"processChunk",
"(",
")",
"{",
"Classifier",
"addedClassifier",
"=",
"null",
";",
"double",
"mse_r",
"=",
"this",
".",
"computeMseR",
"(",
")",
";",
"// Compute weights\r",
"double",
"candidateClassifierWeight",
"=",
"1.0",
"/",
"(",
"mse_r"... | Processes a chunk of instances.
This method is called after collecting a chunk of examples. | [
"Processes",
"a",
"chunk",
"of",
"instances",
".",
"This",
"method",
"is",
"called",
"after",
"collecting",
"a",
"chunk",
"of",
"examples",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/meta/AccuracyUpdatedEnsemble.java#L177-L213 |
29,087 | Waikato/moa | moa/src/main/java/moa/classifiers/meta/AccuracyUpdatedEnsemble.java | AccuracyUpdatedEnsemble.computeMse | protected double computeMse(Classifier learner, Instances chunk) {
double mse_i = 0;
double f_ci;
double voteSum;
for (int i = 0; i < chunk.numInstances(); i++) {
try {
voteSum = 0;
for (double element : learner.getVotesForInstance(chunk.instance(i))) {
voteSum += element;
}
... | java | protected double computeMse(Classifier learner, Instances chunk) {
double mse_i = 0;
double f_ci;
double voteSum;
for (int i = 0; i < chunk.numInstances(); i++) {
try {
voteSum = 0;
for (double element : learner.getVotesForInstance(chunk.instance(i))) {
voteSum += element;
}
... | [
"protected",
"double",
"computeMse",
"(",
"Classifier",
"learner",
",",
"Instances",
"chunk",
")",
"{",
"double",
"mse_i",
"=",
"0",
";",
"double",
"f_ci",
";",
"double",
"voteSum",
";",
"for",
"(",
"int",
"i",
"=",
"0",
";",
"i",
"<",
"chunk",
".",
... | Computes the MSE of a learner for a given chunk of examples.
@param learner classifier to compute error
@param chunk chunk of examples
@return the computed error. | [
"Computes",
"the",
"MSE",
"of",
"a",
"learner",
"for",
"a",
"given",
"chunk",
"of",
"examples",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/meta/AccuracyUpdatedEnsemble.java#L251-L279 |
29,088 | Waikato/moa | moa/src/main/java/moa/classifiers/meta/AccuracyUpdatedEnsemble.java | AccuracyUpdatedEnsemble.trainOnChunk | private void trainOnChunk(Classifier classifierToTrain) {
for (int num = 0; num < this.chunkSizeOption.getValue(); num++) {
classifierToTrain.trainOnInstance(this.currentChunk.instance(num));
}
} | java | private void trainOnChunk(Classifier classifierToTrain) {
for (int num = 0; num < this.chunkSizeOption.getValue(); num++) {
classifierToTrain.trainOnInstance(this.currentChunk.instance(num));
}
} | [
"private",
"void",
"trainOnChunk",
"(",
"Classifier",
"classifierToTrain",
")",
"{",
"for",
"(",
"int",
"num",
"=",
"0",
";",
"num",
"<",
"this",
".",
"chunkSizeOption",
".",
"getValue",
"(",
")",
";",
"num",
"++",
")",
"{",
"classifierToTrain",
".",
"tr... | Trains a component classifier on the most recent chunk of data.
@param classifierToTrain
Classifier being trained. | [
"Trains",
"a",
"component",
"classifier",
"on",
"the",
"most",
"recent",
"chunk",
"of",
"data",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/meta/AccuracyUpdatedEnsemble.java#L370-L374 |
29,089 | Waikato/moa | moa/src/main/java/moa/cluster/Clustering.java | Clustering.get | public Cluster get(int index){
if(index < clusters.size()){
return clusters.get(index);
}
return null;
} | java | public Cluster get(int index){
if(index < clusters.size()){
return clusters.get(index);
}
return null;
} | [
"public",
"Cluster",
"get",
"(",
"int",
"index",
")",
"{",
"if",
"(",
"index",
"<",
"clusters",
".",
"size",
"(",
")",
")",
"{",
"return",
"clusters",
".",
"get",
"(",
"index",
")",
";",
"}",
"return",
"null",
";",
"}"
] | get a cluster from the clustering | [
"get",
"a",
"cluster",
"from",
"the",
"clustering"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/cluster/Clustering.java#L224-L229 |
29,090 | Waikato/moa | moa/src/main/java/moa/classifiers/trees/HoeffdingAdaptiveTree.java | HoeffdingAdaptiveTree.filterInstanceToLeaves | public FoundNode[] filterInstanceToLeaves(Instance inst,
SplitNode parent, int parentBranch, boolean updateSplitterCounts) {
List<FoundNode> nodes = new LinkedList<FoundNode>();
((NewNode) this.treeRoot).filterInstanceToLeaves(inst, parent, parentBranch, nodes,
updateSplitter... | java | public FoundNode[] filterInstanceToLeaves(Instance inst,
SplitNode parent, int parentBranch, boolean updateSplitterCounts) {
List<FoundNode> nodes = new LinkedList<FoundNode>();
((NewNode) this.treeRoot).filterInstanceToLeaves(inst, parent, parentBranch, nodes,
updateSplitter... | [
"public",
"FoundNode",
"[",
"]",
"filterInstanceToLeaves",
"(",
"Instance",
"inst",
",",
"SplitNode",
"parent",
",",
"int",
"parentBranch",
",",
"boolean",
"updateSplitterCounts",
")",
"{",
"List",
"<",
"FoundNode",
">",
"nodes",
"=",
"new",
"LinkedList",
"<",
... | New for options vote | [
"New",
"for",
"options",
"vote"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/classifiers/trees/HoeffdingAdaptiveTree.java#L473-L479 |
29,091 | Waikato/moa | moa/src/main/java/com/yahoo/labs/samoa/instances/Range.java | Range.setRange | public void setRange(String range) {
String single = range.trim();
int hyphenIndex = range.indexOf('-');
if (hyphenIndex > 0) {
this.start = rangeSingle(range.substring(0, hyphenIndex));
this.end = rangeSingle(range.substring(hyphenIndex + 1));
} else {
... | java | public void setRange(String range) {
String single = range.trim();
int hyphenIndex = range.indexOf('-');
if (hyphenIndex > 0) {
this.start = rangeSingle(range.substring(0, hyphenIndex));
this.end = rangeSingle(range.substring(hyphenIndex + 1));
} else {
... | [
"public",
"void",
"setRange",
"(",
"String",
"range",
")",
"{",
"String",
"single",
"=",
"range",
".",
"trim",
"(",
")",
";",
"int",
"hyphenIndex",
"=",
"range",
".",
"indexOf",
"(",
"'",
"'",
")",
";",
"if",
"(",
"hyphenIndex",
">",
"0",
")",
"{",... | Sets the range from a string representation.
@param range the start and end string | [
"Sets",
"the",
"range",
"from",
"a",
"string",
"representation",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/com/yahoo/labs/samoa/instances/Range.java#L39-L56 |
29,092 | Waikato/moa | moa/src/main/java/com/yahoo/labs/samoa/instances/Range.java | Range.rangeSingle | protected /*@pure@*/ int rangeSingle(/*@non_null@*/String singleSelection) {
String single = singleSelection.trim();
if (single.toLowerCase().equals("first")) {
return 0;
}
if (single.toLowerCase().equals("last") || single.toLowerCase().equals("-1")) {
return -1;... | java | protected /*@pure@*/ int rangeSingle(/*@non_null@*/String singleSelection) {
String single = singleSelection.trim();
if (single.toLowerCase().equals("first")) {
return 0;
}
if (single.toLowerCase().equals("last") || single.toLowerCase().equals("-1")) {
return -1;... | [
"protected",
"/*@pure@*/",
"int",
"rangeSingle",
"(",
"/*@non_null@*/",
"String",
"singleSelection",
")",
"{",
"String",
"single",
"=",
"singleSelection",
".",
"trim",
"(",
")",
";",
"if",
"(",
"single",
".",
"toLowerCase",
"(",
")",
".",
"equals",
"(",
"\"f... | Translates a single string selection into it's internal 0-based
equivalent.
@param single the string representing the selection (eg: 1 first last)
@return the number corresponding to the selected value | [
"Translates",
"a",
"single",
"string",
"selection",
"into",
"it",
"s",
"internal",
"0",
"-",
"based",
"equivalent",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/com/yahoo/labs/samoa/instances/Range.java#L65-L79 |
29,093 | Waikato/moa | moa/src/main/java/moa/clusterers/outliers/utils/mtree/utils/Utils.java | Utils.minMax | public static <T extends Comparable<T>> Pair<T> minMax(Iterable<T> items) {
Iterator<T> iterator = items.iterator();
if(!iterator.hasNext()) {
return null;
}
T min = iterator.next();
T max = min;
while(iterator.hasNext()) {
T item = iterator.next();
if(item.compareTo(min) < 0) {
min = ite... | java | public static <T extends Comparable<T>> Pair<T> minMax(Iterable<T> items) {
Iterator<T> iterator = items.iterator();
if(!iterator.hasNext()) {
return null;
}
T min = iterator.next();
T max = min;
while(iterator.hasNext()) {
T item = iterator.next();
if(item.compareTo(min) < 0) {
min = ite... | [
"public",
"static",
"<",
"T",
"extends",
"Comparable",
"<",
"T",
">",
">",
"Pair",
"<",
"T",
">",
"minMax",
"(",
"Iterable",
"<",
"T",
">",
"items",
")",
"{",
"Iterator",
"<",
"T",
">",
"iterator",
"=",
"items",
".",
"iterator",
"(",
")",
";",
"i... | Identifies the minimum and maximum elements from an iterable, according
to the natural ordering of the elements.
@param items An {@link Iterable} object with the elements
@param <T> The type of the elements.
@return A pair with the minimum and maximum elements. | [
"Identifies",
"the",
"minimum",
"and",
"maximum",
"elements",
"from",
"an",
"iterable",
"according",
"to",
"the",
"natural",
"ordering",
"of",
"the",
"elements",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/outliers/utils/mtree/utils/Utils.java#L43-L63 |
29,094 | Waikato/moa | moa/src/main/java/moa/clusterers/outliers/utils/mtree/utils/Utils.java | Utils.randomSample | public static <T> List<T> randomSample(Collection<T> collection, int n) {
List<T> list = new ArrayList<T>(collection);
List<T> sample = new ArrayList<T>(n);
Random random = new Random();
while(n > 0 && !list.isEmpty()) {
int index = random.nextInt(list.size());
sample.add(list.get(index));
int indexL... | java | public static <T> List<T> randomSample(Collection<T> collection, int n) {
List<T> list = new ArrayList<T>(collection);
List<T> sample = new ArrayList<T>(n);
Random random = new Random();
while(n > 0 && !list.isEmpty()) {
int index = random.nextInt(list.size());
sample.add(list.get(index));
int indexL... | [
"public",
"static",
"<",
"T",
">",
"List",
"<",
"T",
">",
"randomSample",
"(",
"Collection",
"<",
"T",
">",
"collection",
",",
"int",
"n",
")",
"{",
"List",
"<",
"T",
">",
"list",
"=",
"new",
"ArrayList",
"<",
"T",
">",
"(",
"collection",
")",
";... | Randomly chooses elements from the collection.
@param collection The collection.
@param n The number of elements to choose.
@param <T> The type of the elements.
@return A list with the chosen elements. | [
"Randomly",
"chooses",
"elements",
"from",
"the",
"collection",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/outliers/utils/mtree/utils/Utils.java#L73-L88 |
29,095 | Waikato/moa | moa/src/main/java/moa/gui/visualization/GraphCanvas.java | GraphCanvas.updateMinMaxValues | private boolean updateMinMaxValues() {
double min_y_value_new = min_y_value;
double max_y_value_new = max_y_value;
double max_x_value_new = max_x_value;
if (measure0 != null && measure1 != null) {
min_y_value_new = Math.min(measure0.getMinValue(measureSelected), measure1.get... | java | private boolean updateMinMaxValues() {
double min_y_value_new = min_y_value;
double max_y_value_new = max_y_value;
double max_x_value_new = max_x_value;
if (measure0 != null && measure1 != null) {
min_y_value_new = Math.min(measure0.getMinValue(measureSelected), measure1.get... | [
"private",
"boolean",
"updateMinMaxValues",
"(",
")",
"{",
"double",
"min_y_value_new",
"=",
"min_y_value",
";",
"double",
"max_y_value_new",
"=",
"max_y_value",
";",
"double",
"max_x_value_new",
"=",
"max_x_value",
";",
"if",
"(",
"measure0",
"!=",
"null",
"&&",
... | returns true when values have changed | [
"returns",
"true",
"when",
"values",
"have",
"changed"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/visualization/GraphCanvas.java#L148-L173 |
29,096 | Waikato/moa | moa/src/main/java/moa/gui/visualization/GraphCanvas.java | GraphCanvas.addEvents | private void addEvents() {
if (clusterEvents != null && clusterEvents.size() > eventCounter) {
ClusterEvent ev = clusterEvents.get(eventCounter);
eventCounter++;
JLabel eventMarker = new JLabel(ev.getType().substring(0, 1));
eventMarker.setPreferredSize(new Dimen... | java | private void addEvents() {
if (clusterEvents != null && clusterEvents.size() > eventCounter) {
ClusterEvent ev = clusterEvents.get(eventCounter);
eventCounter++;
JLabel eventMarker = new JLabel(ev.getType().substring(0, 1));
eventMarker.setPreferredSize(new Dimen... | [
"private",
"void",
"addEvents",
"(",
")",
"{",
"if",
"(",
"clusterEvents",
"!=",
"null",
"&&",
"clusterEvents",
".",
"size",
"(",
")",
">",
"eventCounter",
")",
"{",
"ClusterEvent",
"ev",
"=",
"clusterEvents",
".",
"get",
"(",
"eventCounter",
")",
";",
"... | check if there are any new events in the event list and add them to the plot | [
"check",
"if",
"there",
"are",
"any",
"new",
"events",
"in",
"the",
"event",
"list",
"and",
"add",
"them",
"to",
"the",
"plot"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/visualization/GraphCanvas.java#L203-L220 |
29,097 | Waikato/moa | moa/src/main/java/moa/evaluation/BasicMultiTargetPerformanceRelativeMeasuresEvaluator.java | BasicMultiTargetPerformanceRelativeMeasuresEvaluator.addResult | @Override
public void addResult(Example<Instance> example, double[] classVotes) {
Prediction p=new MultiLabelPrediction(1);
p.setVotes(classVotes);
addResult(example, p);
} | java | @Override
public void addResult(Example<Instance> example, double[] classVotes) {
Prediction p=new MultiLabelPrediction(1);
p.setVotes(classVotes);
addResult(example, p);
} | [
"@",
"Override",
"public",
"void",
"addResult",
"(",
"Example",
"<",
"Instance",
">",
"example",
",",
"double",
"[",
"]",
"classVotes",
")",
"{",
"Prediction",
"p",
"=",
"new",
"MultiLabelPrediction",
"(",
"1",
")",
";",
"p",
".",
"setVotes",
"(",
"class... | only for one output | [
"only",
"for",
"one",
"output"
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/evaluation/BasicMultiTargetPerformanceRelativeMeasuresEvaluator.java#L152-L157 |
29,098 | Waikato/moa | moa/src/main/java/moa/gui/visualization/ParamGraphCanvas.java | ParamGraphCanvas.setGraph | public void setGraph(MeasureCollection[] measures, MeasureCollection[] measureStds,
double[] variedParamValues, Color[] colors) {
this.measures = measures;
this.variedParamValues = variedParamValues;
((GraphScatter) this.plotPanel).setGraph(measures, measureStds,
vari... | java | public void setGraph(MeasureCollection[] measures, MeasureCollection[] measureStds,
double[] variedParamValues, Color[] colors) {
this.measures = measures;
this.variedParamValues = variedParamValues;
((GraphScatter) this.plotPanel).setGraph(measures, measureStds,
vari... | [
"public",
"void",
"setGraph",
"(",
"MeasureCollection",
"[",
"]",
"measures",
",",
"MeasureCollection",
"[",
"]",
"measureStds",
",",
"double",
"[",
"]",
"variedParamValues",
",",
"Color",
"[",
"]",
"colors",
")",
"{",
"this",
".",
"measures",
"=",
"measures... | Sets the scatter graph.
@param measures
information about the curves
@param measureStds
standard deviation for the measures
@param variedParamValues
values of the varied parameter
@param colors
color encoding for the param array | [
"Sets",
"the",
"scatter",
"graph",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/gui/visualization/ParamGraphCanvas.java#L62-L69 |
29,099 | Waikato/moa | moa/src/main/java/moa/clusterers/CobWeb.java | CobWeb.getVotesForInstance | public double[] getVotesForInstance(Instance instance) {
//public int clusterInstance(Instance instance) {//throws Exception {
CNode host = m_cobwebTree;
CNode temp = null;
determineNumberOfClusters();
if (this.m_numberOfClusters < 1) {
return (new double[0]);
... | java | public double[] getVotesForInstance(Instance instance) {
//public int clusterInstance(Instance instance) {//throws Exception {
CNode host = m_cobwebTree;
CNode temp = null;
determineNumberOfClusters();
if (this.m_numberOfClusters < 1) {
return (new double[0]);
... | [
"public",
"double",
"[",
"]",
"getVotesForInstance",
"(",
"Instance",
"instance",
")",
"{",
"//public int clusterInstance(Instance instance) {//throws Exception {",
"CNode",
"host",
"=",
"m_cobwebTree",
";",
"CNode",
"temp",
"=",
"null",
";",
"determineNumberOfClusters",
... | Classifies a given instance.
@param instance the instance to be assigned to a cluster
@return the number of the assigned cluster as an interger
if the class is enumerated, otherwise the predicted value
@throws Exception if instance could not be classified
successfully | [
"Classifies",
"a",
"given",
"instance",
"."
] | 395982e5100bfe75a3a4d26115462ce2cc74cbb0 | https://github.com/Waikato/moa/blob/395982e5100bfe75a3a4d26115462ce2cc74cbb0/moa/src/main/java/moa/clusterers/CobWeb.java#L815-L844 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.