I had obtained the index of training set and testing set with code below. df = pandas.read_pickle(filepath + filename) kf = KFold(n_splits = n_splits, shuffle = shuffle, random_state = randomState...

Based on Sklearn Docs: Is it possible to force the use of StratifiedKFold? How can I know which KFold has been used?

I am new to pytorch and are trying to implement a feed forward neural network to classify the mnist data set. I have some problems when trying to use cross-validation. My data has the following sha...

I am using different cross validation method. I first use k fold method on my code and it was perfectly well but when I use repeatedstratifiedkfold method it gives me this error TypeError: Singleto...

I use this code to test KFold and StratifiedKFold. import numpy as np from sklearn.model_selection import KFold,StratifiedKFold X = np.array([ [1,2,3,4], [11,12,13,14], [21,22,23,24], [31,32,3...

It gives that memory error but memory capacity is never reached. I have 60 GB of ram on the SSH and the full dataset process consumes 30 I am trying to train an autoendcoder with k-fold. Without k-...

What I am trying to do? I am trying to use StratifiedKFold() in GridSearchCV(). Then, what does confuse me? When we use K Fold Cross Validation, we just pass the number of CV inside GridSearchCV...

I have a data frame with 4 different groups of features. I need to create 4 different models with these four different feature groups and combine them with the ensemble voting classifier. Further...

I'm spliting some data in train and test set according to group values. How can I do this in order to have balanced data? In order to solve a binary classification task I have 100 samples, each on...

I'm making a code to solve a simple problem of predict the probability of an item missing from an inventory. I'm using the XGBoost prediction model to do this. I have the data split in two .csv f...