# Run this application in a virtual environment # [venv] python catsdogs.py --dataset kaggle_dogs_vs_cats # kaggle_dogs_vs_cats directory contains the 25000 images (cats and dogs) # import the necessary packages from sklearn.preprocessing import LabelEncoder from ...
preprocessing import LabelEncoder from sklearn.utils import indexable from sklearn.utils import indexable, check_random_state from sklearn.utils.validation import _num_samples Expand All @@ -29,12 +29,18 @@ def _split_weighted_sample(self, X, y, sample_weight, is_stratified=False): else: ...