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H: BIO tagging software
I would like to label character data with BIO tags as part of an active learning process on unlabelled data. I am assuming there are open source GUI tools available which I can use to make this easier - i.e. present the string to be labeled and some way of tagging characters from a predefined s... |
H: When to One-Hot encode categorical data when following Crisp-DM
I have a dataset that contains 15 categorical features (2 and 3 level factors which are non-ordinal) and 3 continuous numeric features. Seeing as most machine learning algorithms require numerical data as input features, and actually automatically One-... |
H: How to extract true positives data (complete row with data) after training and testing from test dataset?
How do you extract true positive data from testing data after training and testing?
For example, in the test data, I have two rows and one row is true positives and the other is false negatives. However, I woul... |
H: Is CNN permutation equivariant?
If I use stacked CNN layers with 3x3 kernels, zero padding, and with no pooling layers, the output feature map will consist of feature vectors, each vector of which is related directly to the original 3x3 block of the input image, right?
Therefore, for example, I could send the outpu... |
H: What is lagrangian?
I'm watching an SVM tutorial.
At 6:38 he mentions lagrangian, which is a term I'm not familiar with.
So I googled it, hoping to find the Wikipedia article about it, but it seems like this term is actually ambiguous, and Wikipedia suggests several articles.
Which of the suggested articles should ... |
H: Comparing multi-class vs. binary classifiers in predicting a single class
I've pretty much read the majority of similar questions, but I haven't yet found the answer to my question.
Let's say we have n samples of four different labels/classes namely A, B, C, and D. We train two classifiers:
First classifier: we tr... |
H: Creating a valid dataset for obtaining results
I have created a domain-specific dataset, lets say it is relating to python programming topic posts. I have taken data from various places specific to this topic to create positive examples in my dataset. For example, python related subreddits, stack exchange posts tag... |
H: What are the true error and the sample error?
I am a student and I am studying machine learning. I am focusing on the concept of evaluation of an hypotesis.
What I have seen is that there are two types of error: true error and sample error.
The true error of an hypotesis $h$ with respect to a target function $f$ an... |
H: Why my weights are being the same?
To understand how neural networks, and backpropagation are actually working, I've built a small program to do the calculations, but something is definitely wrong, as my weights are the same after gradient descent. In this example the inputs will have two neurons, the outputs will ... |
H: Preparing Dataset Minority Class vs Majority Class
I'm currently doing a binary classification for sentiment prediction. Currently I have the majority class (~90% of the data) as my positive class (labelled 1) and the minority class (~10% of the data) as my negative class (labeled 0). What I'd like to maximize in t... |
H: Which GUI library to use with Deep Learning
I have completed basics Deep Learning course from coursera using Tensorflow and Keras.
Now I want to apply GUI to it.
So which library should i learn:
1.PyQt
2.Kivy
3.Tkinter
Are there libraries which can help to easily create deep learning projects.
AI: It really depends... |
H: Calculating distance between data points when there are more than 3 features in KNN algorithm
I've been reading about K-nearest neighbors algorithm and want to clarify few things.
If we have 2 features we could simply plot it on 2-d plane and calculate distance by using euclidean distance or Manhattan distance.
Whe... |
H: What are "downstream models"?
In the ResNeSt paper they say on page 4:
"despite their great success in image classification, the meta network structures are distinct from each other, which makes it hard for downstream models to build upon."
What are downstream models in this context?
Paper can be found at https://a... |
H: How can I compare the grammatical complexity between two texts using their sentences dependency length?
This is a continuation to the following thread.
I have two texts, common English texts such as news articles and informative texts versus a technical textbook. I want to compare the grammatical complexity between... |
H: My first Neural Network not working
I have just started deep learning and neural networks and when I try the following code, it does not work:
#Import Keras for deep learning
import tensorflow as tf
from tensorflow import keras
#Store the data into a variable
data = keras.datasets.fashion_mnist
#Split the data and ... |
H: Data visualization on three factors
I have three factors,
Income(from source A)，continuous variable
Income(from source B), continuous variable
Happiness index，continuous variable
Suppose I have 500 samples. My goal is to show the influence of both Income(from source A) and Income(from source B) on Happiness index... |
H: Normal equation for linear regression is illogical
Currently I'm taking Andrew Ng's course. He gives a following formula to find solution for linear regression analytically:
$θ = (X^T * X)^{-1} * X^T * у$
He doesn't explain it so I searched for it and found that $(X^T * X)^{-1} * X^T$ is actually a formula of pseud... |
H: Suspiciously good accuracy using neural network
I have a dataset from EEG data that is 24 features (24 electrodes) and 88000 samples with 3 classes, it is normalised and everything and had some noise filtered out via bandpassing.
When I classify with anything but a neural network the accuracy is pretty bad and I am... |
H: Different representations of dendrograms
I have a dendrogram represented in a format I don't understand:
(K_5:1.000030e+00,((K_1:2.000000e-05,(K_2:1.000000e-05,K_3:1.000000e-05):1.000000e-05):1.000000e-05,K_4:3.000000e-05)0.806:1.000000e+00):0.000000e+00;
I am not sure how to interpret the above.
It is an output of... |
H: Which colour channel from a TIFF image do I have to use?
I'm going to use the following dataset to do semantic segmentation with U-Net network.
LGG Segmentation Dataset
This dataset contains brain MR images together with manual FLAIR abnormality segmentation masks. The images were obtained from The Cancer Imaging A... |
H: How would you encode missing pixels in image data?
I am working through an example on the MNIST dataset, and was just curious, if your image input data were missing some pixels, how would you encode it. Since the values are always positive, and normalized between 0 and 1, would it make sense just to encode it as -... |
H: Can someone explain to me the structure of a plain Recurrent Neural Network?
I have seen pictures of RNNs and LTSMs, and they usually look like this:
Here the task is to take a sentence and make a prediction of some sort. What are each of the green squares? Are each of them layers, or does each green square have... |
H: Tensorflow take ages for tf.cond and eval() - python code (sorry but i asked on Stackoverflow but none answer me)
I got a problem with TensorFlow and need your help.
My need is calculating tensordot between a vector: 1x512 named face in my code and a faces data: N x 512 named input_faces_data. The code will return ... |
H: Combining Two CSV's in Jupyter Notebook
I want to combine both CSV files based on Column1, also when combined each element of Column1 of both csv should match and also each row or Please suggest how to reorder Column1 according to another csv.
In Jupyter Notebook
Thank You!
AI: You can try the below code to merge... |
H: How to interpret skimage orientation to straighten images?
I have a bunch of images that I am trying to straighten so the images are horizontal (major axis is horizontal) but I don't understand the orientation output from regionprops method in skimage. How to convert it into degrees ? What is the axis reference for... |
H: Pandas - Avoid boolean result when using groupby()
I have this script:
sectors = df.groupby(['company_sector']).mean()['investment_in_millions']
Output:
I wanted to keep the same groupy() but having a result in "investment_in_millions" column filtered as mean > 10 or another value.
If apply this:
sectors... |
H: How to best read large dataset from disk
I want to solve a task using a ResNet in keras and tensorflow. My Dataset is big, and right now I'm considering my data loading options and trying to determine which one suits the task best.
About the Dataset:
x: arrays of 200x700 cells in range -1.0...1.0, I don't want to ... |
H: Class label prediction in keras sequential model showing different results in confusion matrix
With Keras Sequential Model Prediction
To get Class Labels
we can do
yhat_classes1 = Keras_model.predict_classes(predictors)[:, 0] #this shows deprecated warning in tf==2.3.0
WARNING:tensorflow:From <ipython-input-54-226... |
H: Why training of a neural network will require multiple iterations?
I can't understand why training of a neural network will require multiple iterations (theoretically)?
Can anyone explain why, please?
AI: Solving optimisation problems is difficult, and finding a closed-form solution that finds the optimal point for... |
H: Getting 0 accuracy and NaN mae for all epochs training my NN
Background:
I made a simple game using python library 'Turtle' in which there is a long plank with a ball balanced on top of it. I can press right or left arrow keys to rotate the plank (either clockwise or anticlockwise) which makes the ball roll to the ... |
H: Bidirectional vs. Traditional LSTM
I'm working on image captioning problem, where I need to have an encoder for image and decoder for caption generation. Regarding the decoder, I've found a reference that uses Pytorch LSTM where bidirectional parameter is False. However, I know that bidirectional LSTM is more accur... |
H: How can be proved that the softmax output forms a probability distribution and the sigmoid output does not?
I was reading Nielsen's book and in this part of chapter 3 about the softmax function, he says, just before the following Excercise, that the output of a neural network with a output softmax layers forms a pr... |
H: Understanding declared parameters in my Conv2d layer of my convolutional neural network
I am trying to understand the architecture of my keras model implemented by the sequential model.
Here is a piece of the code :
model = Sequential([
#block1
layers.Conv2D(nfilter,(3,3),padding="same",name="block1_conv1",... |
H: multiple linear regression with 5 records and 25 features
X1 X2 X[...] X25 Y
Q1_2019 23 65 18 32 1,6
Q2_2019 87 32 23 46 1,2
Q3_2019 34 15 63 78 3,2
Q4_2019 85 45 43 65 3,9
Q1_2020 85 43 7... |
H: Can a linear regression model without polynomial features overfit?
I've read in some articles on the internet that linear regression can overfit. However is that possible when we are not using polynomial features? We are just plotting a line trough the data points when we have one feature or a plane when we have tw... |
H: Does mini-batch gradient descent nullify the effect of stratification on the training data set?
In data pre-processing, stratified shuffle is used to ensure that the distribution of the original dataset is reflected in the training, test and validation dataset.
Mini-batch gradient descent uses random shuffling to e... |
H: NER evaluation metric
I'm trying to compare two NER tools on an annotated corpus and I'm not sure which is the best metric to use, as I haven't worked with NER models before. To be more specific, I'm interested in one class only, so I want to evaluate them on that particular class.
AI: A good starting point is to l... |
H: What's Joint Training in Neural Networks?
I'm having a hard time trying to find a good explanation of the process of Joint Training in Neural Networks. I already understand the concepts of Fine Tuning and Feature Extraction, and i know it has to do with the practice of taking a network model that has already been t... |
H: How keras.layers.embedding learn word embeddings?
I was trying some tensorflow tutorials and see that in all of them they use layers.embedding to learn these word embeddings, but how are these learned? , with a NN? which arquitecture? , or word2vec?
Thanks
AI: The keras embedding layer is initialized with random we... |
H: NotFittedError says this StandardScaler instance is not fitted yet while using inverse_transform()
I have a dataset and i have used Support Vector Regression.So i needed to use StandardScaler module from sklearn.preprocessing fro Feature Scaling.
After training my model when i came to predict it was giving a predic... |
H: How does TF-IDF classify a document based on "Score" alloted to each word
I understand how TF-IDF "score" is calculated for each word in a document, but I do not get how can it be used to classify a test document. For example, if the word "Mobile" occurs in two texts, in the training data, one about Business (like ... |
H: Multiple linear regression for multi-dimensional input and output?
Assume that I have $N$ points $x_i,i=1,...,N$ in some $A>1$-dimensional space $\mathbb{R}^A$ with pointwise evaluations of some function $f:\mathbb{R}^A \rightarrow \mathbb{R}^B$, i.e. $f(x_i),i=1,...,N$ where $f(x_i) \in \mathbb{R}^B$.
It is my go... |
H: Is Flatten() layer in keras necessary?
In CNN transfer learning, after applying convolution and pooling,is Flatten() layer necessary?
I have seen an example where after removing top layer of a vgg16 ,first applied layer was GlobalAveragePooling2D() and then Dense().
Is this specific to transfer learning?
This is th... |
H: Predicting financial data (choosing a model)
it is my first time doing something with financial data. I have a dataset with account numbers and some other information about each client (some clients span more than one row since we have info for each month in a different row).
I managed to clean and create some mode... |
H: How to serialize/pickle a spacy ner model?
I have trained a custom SpaCy named entity recognition model. I saved the model to disk using:
nlp.to_disk()
which results in keeping the model in a folder. Is it possible to make the nlp object to a pickle file?
AI: Yes - Here is how to pickle in Python:
import pickle
p... |
H: Improving misclassification for one class in a multi-class classification task
Here I am trying to use 3 convolution layer neural network to classify a set of images (train data: (3249) , validation data: (487), test data: (326))
I have one class which is misclassified and I cannot understand what to do next. I hav... |
H: When a dataset is huge, what do you do to train with all the images on i t?
I'm using Python 3.7.7.
I'm trying to load a lot of NIFTI images using SimplyITK and Numpy from the [BraTS 2019 dataset][1].
This is the code I use to load the images into a numpy array.
import SimpleITK as sitk
def read_nifti_images(imag... |
H: Isn't (steps_per_epoch = total training data/batch size)?
Suppose i have 1000 dog images and my batch size is 10.
It will take 1000/10=100 steps to complete 1 epoch.
So doesn't it mean steps_per_epoch=100 ?
Then why do we have to specify it separately in keras while applying .fit().
AI: As clearly mentioned in the ... |
H: How can access to modify feature_importances of Random Forest Classifier model?
My goal is to extract the feature importances from already trained random forest classifier and transfer them to another classifier. How this can be done? and How can access to modify feature_importances of Random Forest Classifier mode... |
H: What are bias and variance in machine learning?
I am studying machine learning, and I have encountered the concept of bias and variance. I am a university student and in the slides of my professor, the bias is defined as:
$bias = E[error_s(h)]-error_d(h)$
where $h$ is the hypotesis and $error_s(h)$ is the sample er... |
H: Why is Regularization after PCA or Factor Analysis a bad idea?
I have done Factor Analysis on my data and applied various machine learning models on it. I particularly find it giving high MSE value for Ridge and Lasso Regression compared to other models. I want to know the reason why this happens.
AI: In principle,... |
H: Are my features enough?
I am trying to fit a regression model on a non linear data.
The features I have are around 12 and around 800 samples.
With the help of PyCaret, i tried to fit the data on to around 22 model, and then selected the best one (Ada Boost) and then tried further to tune it to get better result.
Ho... |
H: Why does it has a constant val_loss:?
I am working on somr dataset and am implementing a deep neural network. There are some typos that I am not familiar with. strong text
AI: Change the last layer's Neuron count to 2.
model.add(keras.layers.Dense( 2, activation="softmax"))
OR
Change your last layer's activation ... |
H: Which is better: Cross validation or a validation set for hyperparameter optimization?
For hyperparameter optimization I see two approaches:
Splitting the dataset into train, validation and test, and optimize the hyperparameters based on the results of training on the train dataset and evaluating on the validation... |
H: KNN Regression: Distance function and/or vector representation for datetime features
Context: Trying to forecast some sort of consumption value (e.g. water) using datetime features and exogenous variables (like temperature).
Take some datetime features like week days (mon=1, tue=2, ..., sun=7) and months (jan=1, ..... |
H: Significance of Object-Oriented Programming (OOP) in Data Science
Can someone please explain to me the role of Object-Oriented Programming (OOP) and Object-Oriented Design (OOD) in Data Science? I am from a non-computer science background. Do I need to learn these as well to become a Data Scientist? Also, please te... |
H: Tensorflow-keras Image Classifier error while fitting
I was building an image classifier with TensorFlow but I got stuck while fitting the model. Can somebody help me out?
python
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Activation, Fl... |
H: Creating an "unclassified" class in Random Forest
I am trying to classify satellite based images by creating a region of interest and then classifying according to it.
I am using a Jupyter notebook using python to do that.
I used a Random forest classifier and got a nice model and result, but the problem is that th... |
H: Should I keep common stop-words when preprocessing for word embedding?
If I want to construct a word embedding by predicting a target word given context words, is it better to remove stop words or keep them?
the quick brown fox jumped over the lazy dog
or
quick brown fox jumped lazy dog
As a human, I feel like ... |
H: Does convergence of loss function is always guarnteed?
Which of the following is true, given the optimal learning rate?
(i) For convex loss functions (i.e. with a bowl shape), batch gradient descent is guaranteed to eventually converge to the global optimum while stochastic gradient descent is not.
(ii) For convex ... |
H: Autoencoder feature extraction plateau
I am working with a large dataset (approximately 55K observations x 11K features) and trying to perform dimensionality reduction to about 150 features. So far, I tried PCA, LDA, and autoencoder. The autoencoder that I tried was 12000-8000-5000-100-500-250-150-, all layers were... |
H: Classifiers and accuracy
I would like to ask you how to use classifier and determine accuracy of models.
I have my dataset and I already cleaned the text (remove stopwords, punctuation, removed empty rows,...).
Then I split it into train and test.
Since I want to determine if an email is spam or not, I have used th... |
H: Not enough memory for operations with Pandas
Wes McKinney, the author of Pandas, writes in his blog that
"... my rule of thumb for pandas is that you should have 5 to 10 times as much RAM as the size of your dataset. So if you have a 10 GB dataset, you should really have about 64, preferably 128 GB of RAM if you wa... |
H: Is a test set necessary after cross validation on training set?
I'd like to cite a paragraph from the book Hands On Machine Learning with Scikit Learn and TensorFlow by Aurelien Geron regarding evaluating on a final test set after hyperparameter tuning on the training set using k-fold cross validation:
"The perfor... |
H: Is there any model agnostic way to calculate the weight importance for neural networks given a set of inputs?
I was curious if it's possible to calculate what weights are important and what weights are redundant (or have high redundancy) for separate tasks in neural networks?
And if this is doable in a model agnost... |
H: High Cross Validation Score on Training Set, High Score on Test Set, But Low Score on Kaggle?
I've been trying to complete this regression task on Kaggle. As usual they gave a train.csv(with response variable) and a test.csv (without response variable) file for us to train the model and compute our predictions, res... |
H: Dropping one category for regularized linear models
While reviewing the sklearn's OneHotEncoder documentation (attached below) I noticed that when applying regularization (e.g., lasso, ridge, etc.) it is not recommended to drop the first category. While I understand why dropped the first category prevents collinear... |
H: Dose finding slope/intercept using the formula of m,b gives best fit line always In linear regression?
In liner regression We have to fit different lines and chose one with minimum error so What is the motive of having a formula for m,b that can give slope and intercept value in the regression line ,when it cannot ... |
H: How to insert two features in a model when a feature only applies to a certain group in the model
I'm building a machine learning model in Python to predict soccer player values. Consider the following feature columns of the dataframe:
[features]
---------------------------------
position | goals | goals_c... |
H: What is major difference between different dimensionality reduction algorithms?
I find many algorithms are used for dimensionality reduction. The more commonly used ones (e.g. on this page ) are:
Principal component analysis (PCA).
Factor Analysis
Independent component analysis (ICA).
Non-negative matrix factorizat... |
H: Semantic networks: word2vec?
I have some doubts on how to represent the relationships between words in texts.
Let’s suppose I have two sentences like these:
Angela Merkel is a German politician who has been Chancellor of Germany since 2005.
What I would expect is a connection between name Angela and Merkel (Angela... |
H: Estimating average daily consumption with samples randomly scattered in time
I want to estimate my daily water consumption. I have taken pictures of the water meters (total m3 used since last reset) every now and then, but without any regularity. There can be a difference of a few days to several weeks between samp... |
H: Predicting time series data
I have a dataset as following:
This is test case 1. My goal is to fill the missing years data. As the age sex and smoking is not changing so I have to predict the condition and percent data for year 0 to all the way 54. I found high correlation between condition and percent variable. Th... |
H: Train a model to determine that the probability of an event given a set of features is higher than when given a different set of features
I have a data set of attempted phone calls.
I have a set of features, say, hour of day, and zip code.
I have a label indicating whether the callee picked up the phone or not.
I w... |
H: What is an autoencoder?
I am a student and I am studying machine learning. I am focusing on deep generative models, and in particular to autoencoders and variational autoencoders (VAE).
I am trying to understand the concept, but I am having some problems.
So far, I have understood that an autoencoder takes an input... |
H: Categorical cross-entropy works wrong with one-hot encoded features
I'n struggling with categorical_crossentropy problem with one-hot encoding data. The problem is in unchanged output of code presenting below:
inputs = keras.Input(shape=(1190,), sparse=True)
lay_1 = layers.Dense(1190, activa... |
H: Setting sparse=True in Scikit Learn OneHotEncoder does not reduce memory usage
I have a dataset that consists of 85 feature columns and 13195 rows. Approximately 50 of these features are categorical features which I encoded using OneHotEncoder. I was reading this article about sparse data sets and was intrigued to ... |
H: Understanding how convolutional layers work
After working with a CNN using Keras and the Mnist dataset for the well-know hand written digit recognition problem, I came up with some questions about how the convolutional layer work. I can understand what the convolution process is.
My first question is: What are the... |
H: Build Deep Belief Autoencoder for Dimensionality Reduction
I'm working with a large dataset (about 50K observations x 11K features) and I'd like to reduce the dimensionality. This will eventually be used for multi-class classification, so I'd like to extract features that are useful for separating the data. Thus fa... |
H: What common/simple problem would work well as a web app?
Context
I'm currently writing a simple tutorial to demonstrate a tool to data scientists and analysts that turns Jupyter Notebooks into web apps. Basically, it discusses setting up the web app as a front end, running some code in the notebook and then returni... |
H: Reduce the risk of numerical underflow
We use log-likelihood (called as lambda) to reduce the risk of numerical underflow (in context of sentiment analysis using Naive Bayes).
What does "reduce the risk of numerical underflow" means?
AI: Arithmetic underflow can happen if the result of a calculation is a number sma... |
H: best approach to embed random length sequences of words as a fixed size vector without having a maximum length?
I have a dataset of sentences in a non-English language like:
word1 word2 word3 word62
word5 word1 word2
and the length of each sentence is not fixed.
Now, I want to represent each sentence as a fixed... |
H: Python - accessing dictionary values for math operations
I have this dictionary:
stocks = {'FB': 255, 'AAPL': 431, 'TSLA': 1700}
and this script:
shares = input('How many shares? ')
stock = input('What\'s the stock? ')
for name in stocks.keys():
ticker = (stocks[name])
if name == stock:
print('The... |
H: Does LSTM without delayed inputs work as a deep net?
I want to predict a multivariate time series. My time series is $a_1(t),...,a_k(t)$ and I want to predict $a_k(t)$. I use the following keras LSTM:
model = Sequential()
model.add(LSTM(90,return_sequences=True,input_shape=(train_X.shape[1], train_X.shape[2])))
mod... |
H: Avoiding Overfitting with a large LSTM net on a small amount of data
I'm reposting this question from AI.SE here as I think it was maybe off-topic for AI.SE...
1. Context
I'm studying Health-Monitoring techniques, and I practice on the C-MAPSS dataset. The goal is to predict the Remaining Useful Life (RUL) of an en... |
H: Image multi class classifier CNN
I have a problem, im designing a multiclass classifier to classify medic images, I have to classify in which grade of desease is it, this are 6 grades , each time the joint deforms a little, so, mi original dataset was imabalanced, each class have like 16 to 200 images that are ver... |
H: Regression and Classification, which is better in financial market price prediction?
I want to use a model to trade in finanical market.
which i have several features, like macd, rsi, or other common features.
and my target is to make a tradeable predict in every time point.
so my target can be:
yield in a fixed t... |
H: How to model the probability of detecting an image, given it is seen multiple times
Are there any existing methods/models describing the probability of an object being detected by a computer vision algorithm given it is seen $n$ times at similar angles and orientations? I know that an autonomous car may, for exampl... |
H: Which policy gradient method is used for continuous action spaces?
Which policy gradient method is used that deals with continuous action spaces?
AI: You can use Soft Actor Critic or PPO from the same website. Most PG methods can be used in discrete and/or continuous action spaces. |
H: Rescale parameter in data augmentation
I'm a little bit lost about the rescale parameter in the ImageDatagenerator function.
I know that the rescale argument by itself does not augment my data and that by doing rescale=1./255 it will convert the pixels in range [0,255] to range [0,1].
Currently, I'm only using rand... |
H: Suitable metric choice for imbalanced multi-class dataset (classes have equal importance)
What type of metrics I should use to evaluate my classification models, given that I have two imbalanced multi-class datasets (21 and 16 classes, respectively) where all classes have equal importance?
I am somehow convinced wi... |
H: Is it a good idea to combine fine tuning and feature extraction techniques?
I have a normal/tumor medical images dataset and, for the same patients, also the relative genomics, and my goal is to predict if a patient has a tumor by combining all the information.
To achieve this, I am using a ResNet50 with imagenet w... |
H: KFold cross validation ambiguity
I just studied K-Fold cross validation technique for finding model parameters and something seemed to be very confusing. Every tutorial I follow says that for K-Fold validation, the whole dataset will be split into K portions and K models will be fit with one portion as validation d... |
H: Max Pooling in first Layer of CNN
I am seeing, in all the notebooks that I found, that Max Pooling is never used in the first layer of a CNN. Why this? Is it a convention among data scientist to do not use max pooling in the first layer? Or is it an error to use in the first layer?
AI: The purpose of max pooling op... |
H: Warning when plotting confusion matrix with all sample of one class
I have two arrays: the first one with all the correct labels (they are all set to zero since each sample belong to the same class) and another one with all the labels predicted by my neural network. What I want do to is plot a simple confusion matr... |
H: How to use random forest with large number of categorical features and categories?
I have 2 features productName and productCategory , both of them are strings. I have a category named supplier. There are 4000 suppliers and 500,000 items in test data. I don't think one hot encoding will be a good approach to deal w... |
H: Difference between bagging and pasting?
I found the definition:
Bagging is to use the same training for every predictor, but to train them on
different random subsets of the training set.
When sampling is performed with replacement, this method is
called bagging (short for bootstrap aggregating).
When sampling ... |
H: How to best visualise two sets of data over several years?
I have a set of data on crime statistics by police force and year, and another set of data showing police workforce numbers over the same period. I am trying to determine the best way to show this data. I have tried three alternatives but looking for prefer... |
H: Encode the days of week as numeric variable
I would like to understand if there is the possibility to encode the days of the week as a single numerical column to preserve the ordinal relationship between the days.
My task is a classification task.
So, something like this:
Monday: 0
Thrusday: 1
Wednesday: 2
...
Sun... |
H: Hi, im currently working for a company that has some inventory control problems
First, I was asked by the manager to make a plot showing produced vs received items, its a multistage process so we are only in charge of one of the steps which is designing, I made the plot comparing Received cases vs produced here in ... |
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