k-fold crossvalidation with sklearn
from sklearn.model_selection import KFold kf = KFold(n_splits=2) kf.split(df_train) step = 0 # set counter to 0 for train_index, val_index in kf.split(df_train): # for each fold step = step + 1 # update counter print(‘Step ‘, step) features_fold_train = df_train.iloc[train_index, [4, 5]] # features matrix of training data (of this step) features_fold_val = df_train.iloc[val_index, [4, 5]]…