l have a dataset of 200 examples with 10 classes. l would like to split the dataset into training set 50% and test set 50%.
for each class, l have 20 examples. Hence, l would like to get for each class : 10 training examples and 10 test examples.
Here are my classes :
classes=['BenchPress', 'ApplyLipstick', 'BabyCrawling', 'BandMarching', 'Archery', 'Basketball', 'ApplyEyeMakeup', 'BalanceBeam', 'BaseballPitch', 'BasketballDunk']
l tried the following :
from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(final_data, true_label, test_size=0.50, random_state=42)
However it returns a 50% training set and 50 % test set, without respecting the proportion for each class (l would like to get 10 examples in test set and 10 examples in training set for each class). Here is the resulted splitting :