_id stringlengths 2 7 | title stringlengths 3 151 | partition stringclasses 3
values | text stringlengths 83 13k | language stringclasses 1
value | meta_information dict |
|---|---|---|---|---|---|
q26800 | Parser.parseUnknown | train | private function parseUnknown(&$var, BasicObject $o)
{
$o->type = 'unknown';
$this->applyPlugins($var, $o, self::TRIGGER_SUCCESS);
return $o;
} | php | {
"resource": ""
} |
q26801 | Parser.applyPlugins | train | private function applyPlugins(&$var, BasicObject &$o, $trigger)
{
$break_stash = $this->parse_break;
/** @var bool Psalm bug workaround */
$this->parse_break = false;
$plugins = array();
if (isset($this->plugins[$o->type][$trigger])) {
$plugins = $this->plugins... | php | {
"resource": ""
} |
q26802 | Plugin.renderLockedHeader | train | public function renderLockedHeader(BasicObject $o, $content)
{
$header = '<dt class="kint-parent kint-locked">';
if (RichRenderer::$access_paths && $o->depth > 0 && $ap = $o->getAccessPath()) {
$header .= '<span class="kint-access-path-trigger" title="Show access path">⇄</span>';
... | php | {
"resource": ""
} |
q26803 | ColorRepresentation.hslToRgb | train | public static function hslToRgb($h, $s, $l)
{
if (\min($h, $s, $l) < 0) {
throw new InvalidArgumentException('The parameters for hslToRgb should be no less than 0');
}
if ($h > 360 || \max($s, $l) > 100) {
throw new InvalidArgumentException('The parameters for hslToR... | php | {
"resource": ""
} |
q26804 | ColorRepresentation.rgbToHsl | train | public static function rgbToHsl($red, $green, $blue)
{
if (\min($red, $green, $blue) < 0) {
throw new InvalidArgumentException('The parameters for rgbToHsl should be no less than 0');
}
if (\max($red, $green, $blue) > 0xFF) {
throw new InvalidArgumentException('The p... | php | {
"resource": ""
} |
q26805 | ColorRepresentation.hueToRgb | train | private static function hueToRgb($m1, $m2, $hue)
{
$hue = ($hue < 0) ? $hue + 1 : (($hue > 1) ? $hue - 1 : $hue);
if ($hue * 6 < 1) {
return $m1 + ($m2 - $m1) * $hue * 6;
}
if ($hue * 2 < 1) {
return $m2;
}
if ($hue * 3 < 2) {
retur... | php | {
"resource": ""
} |
q26806 | BasicObject.blank | train | public static function blank($name = null, $access_path = null)
{
$o = new self();
$o->name = $name;
$o->access_path = $access_path;
return $o;
} | php | {
"resource": ""
} |
q26807 | DocstringRepresentation.getDocstringWithoutComments | train | public function getDocstringWithoutComments()
{
if (!$this->contents) {
return null;
}
$string = \substr($this->contents, 3, -2);
$string = \preg_replace('/^\\s*\\*\\s*?(\\S|$)/m', '\\1', $string);
return \trim($string);
} | php | {
"resource": ""
} |
q26808 | XmlPlugin.xmlToDOMDocument | train | protected static function xmlToDOMDocument($var, $parent_path)
{
// There's no way to check validity in DOMDocument without making errors. For shame!
if (!self::xmlToSimpleXML($var, $parent_path)) {
return null;
}
$xml = new DOMDocument();
$xml->loadXML($var);
... | php | {
"resource": ""
} |
q26809 | Mozscape.getPageAuthority | train | public static function getPageAuthority($url = false)
{
$data = static::getCols('34359738368', $url);
return (parent::noDataDefaultValue() == $data) ? $data :
$data['upa'];
} | php | {
"resource": ""
} |
q26810 | Mozscape.getDomainAuthority | train | public static function getDomainAuthority($url = false)
{
$data = static::getCols('68719476736', Helper\Url::parseHost($url));
return (parent::noDataDefaultValue() == $data) ? $data :
$data['pda'];
} | php | {
"resource": ""
} |
q26811 | Mozscape.getMozRank | train | public static function getMozRank($url = false)
{
$data = static::getCols('16384', $url);
return (parent::noDataDefaultValue() == $data) ? $data :
$data['umrp'];
} | php | {
"resource": ""
} |
q26812 | Mozscape.getMozRankRaw | train | public static function getMozRankRaw($url = false)
{
$data = static::getCols('16384', $url);
return (parent::noDataDefaultValue() == $data) ? $data :
number_format($data['umrr'], 16);
} | php | {
"resource": ""
} |
q26813 | SEOstats.getUrl | train | public static function getUrl($url = false)
{
$url = false !== $url ? $url : self::$_url;
return $url;
} | php | {
"resource": ""
} |
q26814 | Url.isRfc | train | public static function isRfc($url)
{
if(isset($url) && 1 < strlen($url)) {
$host = self::parseHost($url);
$scheme = strtolower(parse_url($url, PHP_URL_SCHEME));
if (false !== $host && ($scheme == 'http' || $scheme == 'https')) {
$pattern = '([A-Za-z][A-... | php | {
"resource": ""
} |
q26815 | Services_JSON.utf162utf8 | train | function utf162utf8($utf16)
{
// oh please oh please oh please oh please oh please
if(function_exists('mb_convert_encoding')) {
return mb_convert_encoding($utf16, 'UTF-8', 'UTF-16');
}
$bytes = (ord($utf16{0}) << 8) | ord($utf16{1});
switch(true) {
c... | php | {
"resource": ""
} |
q26816 | Json.decode | train | public static function decode($str, $assoc = false)
{
if (!function_exists('json_decode')) {
$j = self::getJsonService();
return $j->decode($str);
}
else {
return $assoc ? json_decode($str, true) : json_decode($str);
}
} | php | {
"resource": ""
} |
q26817 | Google.getPageRank | train | public static function getPageRank($url = false)
{
// Composer autoloads classes out of the SEOstats namespace.
// The custom autolader, however, does not. So we need to include it first.
if(!class_exists('\GTB_PageRank')) {
require_once realpath(__DIR__ . '/3rdparty/GTB_PageRank... | php | {
"resource": ""
} |
q26818 | Google.getSearchResultsTotal | train | public static function getSearchResultsTotal($url = false)
{
$url = parent::getUrl($url);
$url = sprintf(Config\Services::GOOGLE_APISEARCH_URL, 1, $url);
$ret = static::_getPage($url);
$obj = Helper\Json::decode($ret);
return !isset($obj->responseData->cursor->estimatedResu... | php | {
"resource": ""
} |
q26819 | Sistrix.getVisibilityIndex | train | public static function getVisibilityIndex($url = false)
{
$url = parent::getUrl($url);
$domain = Helper\Url::parseHost($url);
$dataUrl = sprintf(Config\Services::SISTRIX_VI_URL, urlencode($domain));
$html = static::_getPage($dataUrl);
@preg_match_all('#<h3>(.*?)<\/h3>#s... | php | {
"resource": ""
} |
q26820 | Sistrix.getVisibilityIndexByApi | train | public static function getVisibilityIndexByApi($url = false, $db = false)
{
self::guardApiKey();
self::guardApiCredits();
$url = parent::getUrl($url);
$domain = static::getDomainFromUrl($url);
$database = static::getValidDatabase($db);
$dataUrl = sprintf(Config\Serv... | php | {
"resource": ""
} |
q26821 | HttpRequest.getHttpCode | train | public static function getHttpCode($url)
{
$ua = self::getUserAgent();
$curlopt_proxy = self::getProxy();
$curlopt_proxyuserpwd = self::getProxyUserPwd();
$ch = curl_init($url);
curl_setopt_array($ch, array(
CURLOPT_USERAGENT => $ua,
CURLOPT_RET... | php | {
"resource": ""
} |
q26822 | Alexa.getDailyRank | train | public static function getDailyRank($url = false)
{
self::setRankingKeys($url);
if (0 == self::$_rankKeys['1d']) {
return parent::noDataDefaultValue();
}
$xpath = self::_getXPath($url);
$nodes = @$xpath->query("//*[@id='rank']/table/tr[" . self::$_rankKeys['1d'] ... | php | {
"resource": ""
} |
q26823 | Alexa.getGlobalRank | train | public static function getGlobalRank($url = false)
{
/*
self::setRankingKeys($url);
if (0 == self::$_rankKeys['3m']) {
return parent::noDataDefaultValue();
}
*/
$xpath = self::_getXPath($url);
$xpathQueryList = array(
"//*[@id='traffi... | php | {
"resource": ""
} |
q26824 | Alexa.setRankingKeys | train | public static function setRankingKeys($url = false)
{
$xpath = self::_getXPath($url);
$nodes = @$xpath->query("//*[@id='rank']/table/tr");
if (5 == $nodes->length) {
self::$_rankKeys = array(
'1d' => 2,
'7d' => 3,
'1m' => 4,
... | php | {
"resource": ""
} |
q26825 | GaussianMixture.priors | train | public function priors() : array
{
$priors = [];
if (is_array($this->priors)) {
$total = logsumexp($this->priors);
foreach ($this->priors as $class => $probability) {
$priors[$class] = exp($probability - $total);
}
}
return $prio... | php | {
"resource": ""
} |
q26826 | GaussianMixture.initialize | train | protected function initialize(Dataset $dataset) : array
{
$centroids = $this->seeder->seed($dataset, $this->k);
$kernel = new Euclidean();
$clusters = array_fill(0, $this->k, []);
foreach ($dataset as $sample) {
$bestDistance = INF;
$bestCluster = -1;
... | php | {
"resource": ""
} |
q26827 | PReLU.compute | train | protected function compute(Matrix $z) : Matrix
{
if (!$this->alpha) {
throw new RuntimeException('Layer is not initialized.');
}
$alphas = $this->alpha->w();
$computed = [];
foreach ($z as $i => $row) {
$alpha = $alphas[$i];
$activation... | php | {
"resource": ""
} |
q26828 | PReLU.differentiate | train | protected function differentiate(Matrix $z) : Matrix
{
if (!$this->alpha) {
throw new RuntimeException('Layer has not been initlaized.');
}
$alphas = $this->alpha->w();
$gradient = [];
foreach ($z as $i => $row) {
$alpha = $alphas[$i];
... | php | {
"resource": ""
} |
q26829 | RandIndex.comb | train | public static function comb(int $n, int $k = 2) : int
{
return $k === 0 ? 1 : (int) (($n * self::comb($n - 1, $k - 1)) / $k);
} | php | {
"resource": ""
} |
q26830 | Params.ints | train | public static function ints(int $min, int $max, int $n = 10) : array
{
if (($max - $min) < 0) {
throw new InvalidArgumentException('Maximum cannot be'
. ' less than minimum.');
}
if ($n < 1) {
throw new InvalidArgumentException('Cannot generate less'
... | php | {
"resource": ""
} |
q26831 | Params.floats | train | public static function floats(float $min, float $max, int $n = 10) : array
{
if (($max - $min) < 0.) {
throw new InvalidArgumentException('Maximum cannot be'
. ' less than minimum.');
}
if ($n < 1) {
throw new InvalidArgumentException('Cannot generate... | php | {
"resource": ""
} |
q26832 | Params.grid | train | public static function grid(float $min, float $max, int $n = 10) : array
{
if ($min > $max) {
throw new InvalidArgumentException('Max cannot be less'
. ' then min.');
}
if ($n < 2) {
throw new InvalidArgumentException('Cannot generate less'
... | php | {
"resource": ""
} |
q26833 | Params.args | train | public static function args($object) : array
{
if (!is_object($object)) {
throw new InvalidArgumentException('Argument must be'
. ' an object ' . gettype($object) . ' found.');
}
$reflector = new ReflectionClass($object);
$constructor = $reflector->getCo... | php | {
"resource": ""
} |
q26834 | Params.stringify | train | public static function stringify(array $constructor, string $equator = '=', string $separator = ' ') : string
{
$strings = [];
foreach ($constructor as $arg => $param) {
if (is_object($param)) {
$param = self::shortName($param);
}
if (is_array($p... | php | {
"resource": ""
} |
q26835 | CommitteeMachine.train | train | public function train(Dataset $dataset) : void
{
if ($this->type === self::CLASSIFIER or $this->type === self::REGRESSOR) {
if (!$dataset instanceof Labeled) {
throw new InvalidArgumentException('This estimator requires a'
. ' labeled training set.');
... | php | {
"resource": ""
} |
q26836 | CommitteeMachine.decideClass | train | public function decideClass(array $votes)
{
$scores = array_fill_keys($this->classes, 0.);
foreach ($votes as $i => $vote) {
$scores[$vote] += $this->influences[$i];
}
return argmax($scores);
} | php | {
"resource": ""
} |
q26837 | CommitteeMachine.decideAnomaly | train | public function decideAnomaly(array $votes) : int
{
$scores = array_fill(0, 2, 0.);
foreach ($votes as $i => $vote) {
$scores[$vote] += $this->influences[$i];
}
return argmax($scores);
} | php | {
"resource": ""
} |
q26838 | CommitteeMachine._train | train | public function _train(Learner $estimator, Dataset $dataset) : Learner
{
$estimator->train($dataset);
return $estimator;
} | php | {
"resource": ""
} |
q26839 | Deferred.result | train | public function result() : Matrix
{
if (!$this->result) {
$this->result = call_user_func($this->computation);
}
return $this->result;
} | php | {
"resource": ""
} |
q26840 | GaussianNB.train | train | public function train(Dataset $dataset) : void
{
if (!$dataset instanceof Labeled) {
throw new InvalidArgumentException('This Estimator requires a'
. ' Labeled training set.');
}
DatasetIsCompatibleWithEstimator::check($dataset, $this);
$classes = $datas... | php | {
"resource": ""
} |
q26841 | GaussianNB.partial | train | public function partial(Dataset $dataset) : void
{
if (empty($this->weights) or empty($this->means) or empty($this->variances)) {
$this->train($dataset);
return;
}
if (!$dataset instanceof Labeled) {
throw new InvalidArgumentException('This Estimator req... | php | {
"resource": ""
} |
q26842 | BatchNorm.back | train | public function back(Deferred $prevGradient, Optimizer $optimizer) : Deferred
{
if (!$this->beta or !$this->gamma) {
throw new RuntimeException('Layer has not been initilaized.');
}
if (!$this->stdInv or !$this->xHat) {
throw new RuntimeException('Must perform forwar... | php | {
"resource": ""
} |
q26843 | ClassificationTree.terminate | train | protected function terminate(Labeled $dataset) : BinaryNode
{
$n = $dataset->numRows();
$labels = $dataset->labels();
$counts = array_count_values($labels);
$outcome = argmax($counts);
$probabilities = [];
foreach ($counts as $class => $count) {
$prob... | php | {
"resource": ""
} |
q26844 | ClassificationTree.splitImpurity | train | protected function splitImpurity(array $groups) : float
{
$n = array_sum(array_map('count', $groups));
$impurity = 0.;
foreach ($groups as $dataset) {
$k = $dataset->numRows();
if ($k < 2) {
continue 1;
}
$counts = array_cou... | php | {
"resource": ""
} |
q26845 | DataFrame.columnType | train | public function columnType(int $index) : int
{
if (empty($this->samples)) {
throw new RuntimeException('Cannot determine data type'
. ' of an empty data frame.');
}
$sample = reset($this->samples);
if (!isset($sample[$index])) {
throw new Inv... | php | {
"resource": ""
} |
q26846 | DataFrame.columns | train | public function columns() : array
{
if ($this->numRows() > 1) {
return array_map(null, ...$this->samples);
}
$n = $this->numColumns();
$columns = [];
for ($i = 0; $i < $n; $i++) {
$columns[] = array_column($this->samples, $i);
}
ret... | php | {
"resource": ""
} |
q26847 | DataFrame.columnsByType | train | public function columnsByType(int $type) : array
{
$n = $this->numColumns();
$columns = [];
for ($i = 0; $i < $n; $i++) {
if ($this->columnType($i) === $type) {
$columns[$i] = $this->column($i);
}
}
return $columns;
} | php | {
"resource": ""
} |
q26848 | LogisticRegression.partial | train | public function partial(Dataset $dataset) : void
{
if (!$this->network) {
$this->train($dataset);
return;
}
if (!$dataset instanceof Labeled) {
throw new InvalidArgumentException('This estimator requires a'
. ' labeled training set.');
... | php | {
"resource": ""
} |
q26849 | GradientBoost.compatibility | train | public function compatibility() : array
{
$compatibility = array_intersect($this->base->compatibility(), $this->booster->compatibility());
return array_values($compatibility);
} | php | {
"resource": ""
} |
q26850 | GradientBoost.predict | train | public function predict(Dataset $dataset) : array
{
if (empty($this->ensemble)) {
throw new RuntimeException('Estimator has not been trained.');
}
DatasetIsCompatibleWithEstimator::check($dataset, $this);
$predictions = $this->base->predict($dataset);
foreach (... | php | {
"resource": ""
} |
q26851 | TSNE.pairwiseDistances | train | protected function pairwiseDistances(Matrix $samples) : Matrix
{
$distances = [];
foreach ($samples as $a) {
$temp = [];
foreach ($samples as $b) {
$temp[] = $this->kernel->compute($a, $b);
}
$distances[] = $temp;
}
... | php | {
"resource": ""
} |
q26852 | TSNE.highAffinities | train | protected function highAffinities(Matrix $distances) : Matrix
{
$zeros = array_fill(0, count($distances), 0);
$p = [];
foreach ($distances as $i => $row) {
$affinities = $zeros;
$minBeta = -INF;
$maxBeta = INF;
$beta = 1.;
for ($... | php | {
"resource": ""
} |
q26853 | TSNE.gradient | train | protected function gradient(Matrix $p, Matrix $y, Matrix $distances) : Matrix
{
$q = $distances->square()
->divide($this->degrees)
->add(1.)
->pow((1. + $this->degrees) / -2.);
$qSigma = $q->sum()->multiply(2.);
$q = $q->divide($qSigma)
->cli... | php | {
"resource": ""
} |
q26854 | BootstrapAggregator.train | train | public function train(Dataset $dataset) : void
{
if ($this->type() === self::CLASSIFIER or $this->type() === self::REGRESSOR) {
if (!$dataset instanceof Labeled) {
throw new InvalidArgumentException('This estimator requires a'
. ' labeled training set.');
... | php | {
"resource": ""
} |
q26855 | Isolator.split | train | public static function split(Dataset $dataset) : self
{
$column = rand(0, $dataset->numColumns() - 1);
$sample = $dataset[rand(0, count($dataset) - 1)];
$value = $sample[$column];
$groups = $dataset->partition($column, $value);
return new self($column, $value, $groups);
... | php | {
"resource": ""
} |
q26856 | MeanShift.estimateRadius | train | public static function estimateRadius(Dataset $dataset, float $percentile = 30., ?Distance $kernel = null) : float
{
if ($percentile < 0. or $percentile > 100.) {
throw new InvalidArgumentException('Percentile must be between'
. " 0 and 100, $percentile given.");
}
... | php | {
"resource": ""
} |
q26857 | MeanShift.assign | train | protected function assign(array $sample) : int
{
$bestDistance = INF;
$bestCluster = -1;
foreach ($this->centroids as $cluster => $centroid) {
$distance = $this->kernel->compute($sample, $centroid);
if ($distance < $bestDistance) {
$bestDistance = $d... | php | {
"resource": ""
} |
q26858 | MeanShift.membership | train | protected function membership(array $sample) : array
{
$membership = $distances = [];
foreach ($this->centroids as $centroid) {
$distances[] = $this->kernel->compute($sample, $centroid);
}
$total = array_sum($distances) ?: EPSILON;
foreach ($distances as $dista... | php | {
"resource": ""
} |
q26859 | LODA.logLikelihood | train | protected function logLikelihood(Matrix $z) : array
{
$likelihoods = array_fill(0, $z->n(), 0.);
foreach ($z as $i => $values) {
[$edges, $counts, $densities] = $this->histograms[$i];
foreach ($values as $j => $value) {
foreach ($edges as $k => $edge... | php | {
"resource": ""
} |
q26860 | GaussianRandomProjector.minDimensions | train | public static function minDimensions(int $n, float $maxDistortion = 0.1) : int
{
return (int) round(4. * log($n)
/ ($maxDistortion ** 2 / 2. - $maxDistortion ** 3 / 3.));
} | php | {
"resource": ""
} |
q26861 | Unlabeled.tail | train | public function tail(int $n = 10) : self
{
return self::quick(array_slice($this->samples, -$n));
} | php | {
"resource": ""
} |
q26862 | Unlabeled.append | train | public function append(Dataset $dataset) : Dataset
{
return self::quick(array_merge($this->samples, $dataset->samples()));
} | php | {
"resource": ""
} |
q26863 | Unlabeled.batch | train | public function batch(int $n = 50) : array
{
$batches = [];
$samples = $this->samples;
foreach (array_chunk($this->samples, $n) as $batch) {
$batches[] = self::quick($batch);
}
return $batches;
} | php | {
"resource": ""
} |
q26864 | ExtraTreeRegressor.split | train | protected function split(Labeled $dataset) : Decision
{
$bestImpurity = INF;
$bestColumn = $bestValue = null;
$bestGroups = [];
$max = $dataset->numRows() - 1;
shuffle($this->columns);
foreach (array_slice($this->columns, 0, $this->maxFeatures) as $column) {
... | php | {
"resource": ""
} |
q26865 | GridSearch.combineGrid | train | public static function combineGrid(array $grid) : array
{
$combinations = [[]];
foreach ($grid as $i => $params) {
$append = [];
foreach ($combinations as $product) {
foreach ($params as $param) {
$product[$i] = $param;
... | php | {
"resource": ""
} |
q26866 | GridSearch.train | train | public function train(Dataset $dataset) : void
{
if (!$dataset instanceof Labeled) {
throw new InvalidArgumentException('This Estimator requires a'
. ' Labeled training set.');
}
DatasetIsCompatibleWithEstimator::check($dataset, $this);
if ($this->logger... | php | {
"resource": ""
} |
q26867 | GridSearch.score | train | public function score(Learner $estimator, Labeled $dataset) : float
{
return $this->validator->test($estimator, $dataset, $this->metric);
} | php | {
"resource": ""
} |
q26868 | Labeled.stack | train | public static function stack(array $datasets) : self
{
$samples = $labels = [];
foreach ($datasets as $dataset) {
if (!$dataset instanceof self) {
throw new InvalidArgumentException('Dataset must be'
. ' an instance of Labeled, ' . get_class($dataset)... | php | {
"resource": ""
} |
q26869 | Labeled.zip | train | public function zip() : array
{
$rows = $this->samples;
foreach ($rows as $i => &$row) {
$row[] = $this->labels[$i];
}
return $rows;
} | php | {
"resource": ""
} |
q26870 | Labeled.label | train | public function label(int $index)
{
if (!isset($this->labels[$index])) {
throw new InvalidArgumentException("Row at offset $index"
. ' does not exist.');
}
return $this->labels[$index];
} | php | {
"resource": ""
} |
q26871 | Labeled.labelType | train | public function labelType() : ?int
{
if (!isset($this->labels[0])) {
return null;
}
return DataType::determine($this->labels[0]);
} | php | {
"resource": ""
} |
q26872 | Labeled.transformLabels | train | public function transformLabels(callable $fn) : void
{
$labels = array_map($fn, $this->labels);
foreach ($labels as $label) {
if (!is_string($label) and !is_numeric($label)) {
throw new RuntimeException('Label must be a string or'
. ' numeric type, ' ... | php | {
"resource": ""
} |
q26873 | Labeled.leave | train | public function leave(int $n = 1) : self
{
if ($n < 0) {
throw new InvalidArgumentException('Cannot leave less than 0 samples.');
}
return $this->splice($n, $this->numRows());
} | php | {
"resource": ""
} |
q26874 | Labeled.randomize | train | public function randomize() : self
{
$order = range(0, $this->numRows() - 1);
shuffle($order);
array_multisort($order, $this->samples, $this->labels);
return $this;
} | php | {
"resource": ""
} |
q26875 | Labeled.filterByColumn | train | public function filterByColumn(int $index, callable $fn) : self
{
$samples = $labels = [];
foreach ($this->samples as $i => $sample) {
if ($fn($sample[$index])) {
$samples[] = $sample;
$labels[] = $this->labels[$i];
}
}
return... | php | {
"resource": ""
} |
q26876 | Labeled.filterByLabel | train | public function filterByLabel(callable $fn) : self
{
$samples = $labels = [];
foreach ($this->labels as $i => $label) {
if ($fn($label)) {
$samples[] = $this->samples[$i];
$labels[] = $label;
}
}
return self::quick($samples, $... | php | {
"resource": ""
} |
q26877 | Labeled.sortByColumn | train | public function sortByColumn(int $index, bool $descending = false)
{
$order = $this->column($index);
array_multisort(
$order,
$this->samples,
$this->labels,
$descending ? SORT_DESC : SORT_ASC
);
return $this;
} | php | {
"resource": ""
} |
q26878 | Labeled.sortByLabel | train | public function sortByLabel(bool $descending = false) : Dataset
{
array_multisort(
$this->labels,
$this->samples,
$descending ? SORT_DESC : SORT_ASC
);
return $this;
} | php | {
"resource": ""
} |
q26879 | Labeled.stratify | train | public function stratify() : array
{
$strata = [];
foreach ($this->_stratify() as $label => $stratum) {
$labels = array_fill(0, count($stratum), $label);
$strata[$label] = self::quick($stratum, $labels);
}
return $strata;
} | php | {
"resource": ""
} |
q26880 | Labeled.split | train | public function split(float $ratio = 0.5) : array
{
if ($ratio <= 0 or $ratio >= 1) {
throw new InvalidArgumentException('Split ratio must be strictly'
. " between 0 and 1, $ratio given.");
}
$n = (int) ($ratio * $this->numRows());
$leftSamples = array_slice... | php | {
"resource": ""
} |
q26881 | Labeled.stratifiedFold | train | public function stratifiedFold(int $k = 10) : array
{
if ($k < 2) {
throw new InvalidArgumentException('Cannot create less than'
. " 2 folds, $k given.");
}
$folds = [];
for ($i = 0; $i < $k; $i++) {
$samples = $labels = [];
fore... | php | {
"resource": ""
} |
q26882 | Labeled._stratify | train | protected function _stratify() : array
{
$strata = [];
foreach ($this->labels as $index => $label) {
$strata[$label][] = $this->samples[$index];
}
return $strata;
} | php | {
"resource": ""
} |
q26883 | Labeled.batch | train | public function batch(int $n = 50) : array
{
$sChunks = array_chunk($this->samples, $n);
$lChunks = array_chunk($this->labels, $n);
$batches = [];
foreach ($sChunks as $i => $samples) {
$batches[] = self::quick($samples, $lChunks[$i]);
}
return $batches... | php | {
"resource": ""
} |
q26884 | Labeled.randomWeightedSubsetWithReplacement | train | public function randomWeightedSubsetWithReplacement(int $n, array $weights) : self
{
if ($n < 1) {
throw new InvalidArgumentException('Cannot generate a'
. " subset of less than 1 sample, $n given.");
}
if (count($weights) !== count($this->samples)) {
... | php | {
"resource": ""
} |
q26885 | FuzzyCMeans.membership | train | protected function membership(array $sample) : array
{
$membership = $deltas = [];
foreach ($this->centroids as $centroid) {
$deltas[] = $this->kernel->compute($sample, $centroid);
}
foreach ($this->centroids as $cluster => $centroid) {
$alpha = $this->kerne... | php | {
"resource": ""
} |
q26886 | Hypersphere.split | train | public static function split(Dataset $dataset, Distance $kernel) : self
{
$samples = $dataset->samples();
$center = Matrix::quick($samples)
->transpose()
->mean()
->asArray();
$distances = [];
foreach ($samples as $sample) {
... | php | {
"resource": ""
} |
q26887 | DummyClassifier.train | train | public function train(Dataset $dataset) : void
{
if (!$dataset instanceof Labeled) {
throw new InvalidArgumentException('This estimator requires a'
. ' labeled training set.');
}
$this->strategy->fit($dataset->labels());
$this->trained = true;
} | php | {
"resource": ""
} |
q26888 | DummyClassifier.predict | train | public function predict(Dataset $dataset) : array
{
if (!$this->trained) {
throw new RuntimeException('The learner has not'
. ' been trained.');
}
$n = $dataset->numRows();
$predictions = [];
for ($i = 0; $i < $n; $i++) {
$pr... | php | {
"resource": ""
} |
q26889 | Pipeline.trained | train | public function trained() : bool
{
return ($this->estimator instanceof Learner
and $this->estimator->trained() and $this->fitted)
or $this->fitted;
} | php | {
"resource": ""
} |
q26890 | Pipeline.train | train | public function train(Dataset $dataset) : void
{
$this->fit($dataset);
if ($this->estimator instanceof Learner) {
$this->estimator->train($dataset);
}
$this->fitted = true;
} | php | {
"resource": ""
} |
q26891 | Pipeline.partial | train | public function partial(Dataset $dataset) : void
{
if ($this->elastic) {
$this->update($dataset);
}
if ($this->estimator instanceof Online) {
$this->estimator->partial($dataset);
}
} | php | {
"resource": ""
} |
q26892 | Pipeline.predict | train | public function predict(Dataset $dataset) : array
{
$this->preprocess($dataset);
return $this->estimator->predict($dataset);
} | php | {
"resource": ""
} |
q26893 | Pipeline.fit | train | protected function fit(Dataset $dataset) : void
{
foreach ($this->transformers as $transformer) {
if ($transformer instanceof Stateful) {
$transformer->fit($dataset);
if ($this->logger) {
$this->logger->info('Fitted '
.... | php | {
"resource": ""
} |
q26894 | Pipeline.update | train | protected function update(Dataset $dataset) : void
{
foreach ($this->transformers as $transformer) {
if ($transformer instanceof Elastic) {
$transformer->update($dataset);
if ($this->logger) {
$this->logger->info('Updated '
... | php | {
"resource": ""
} |
q26895 | Pipeline.preprocess | train | protected function preprocess(Dataset $dataset) : void
{
foreach ($this->transformers as $transformer) {
$dataset->apply($transformer);
}
} | php | {
"resource": ""
} |
q26896 | BinaryNode.children | train | public function children() : Generator
{
if ($this->left) {
yield $this->left;
}
if ($this->right) {
yield $this->right;
}
} | php | {
"resource": ""
} |
q26897 | BinaryNode.height | train | public function height() : int
{
return 1 + max(
$this->left ? $this->left->height() : 0,
$this->right ? $this->right->height() : 0
);
} | php | {
"resource": ""
} |
q26898 | BinaryNode.balance | train | public function balance() : int
{
return ($this->right ? $this->right->height() : 0)
- ($this->left ? $this->left->height() : 0);
} | php | {
"resource": ""
} |
q26899 | BinaryNode.attachLeft | train | public function attachLeft(BinaryNode $node) : void
{
$node->setParent($this);
$this->left = $node;
} | php | {
"resource": ""
} |
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