def load_data_vertical_cv(folder, input_path='user_item_vertical', cut=40, high_cut=100000, seed=1):
    '\n    Same as load_data but only returns random 80% of the training set\n    '
    (user_item_train, user_item_test, user_item_validation) = load_data_vertical(folder, input_path=input_path, cut=cut)
    user_item_train = user_item_train.sample(frac=0.8, random_state=seed)
    user_item_test = user_item_test.sample(frac=1, random_state=seed)
    return (user_item_train, user_item_test, user_item_validation)
Same as load_data but only returns random 80% of the training set
def load_data_vertical_cv(folder, input_path='user_item_vertical', cut=40, high_cut=100000, seed=1):
    '\n    \n    '
    (user_item_train, user_item_test, user_item_validation) = load_data_vertical(folder, input_path=input_path, cut=cut)
    user_item_train = user_item_train.sample(frac=0.8, random_state=seed)
    user_item_test = user_item_test.sample(frac=1, random_state=seed)
    return (user_item_train, user_item_test, user_item_validation)