Here I explore an issue with how sklearn’s paired_cosine_distances function returns erronous values when we have one vector with zero norm. import numpy as np from sklearn.metrics.pairwise import paired_cosine_distances, paired_euclidean_distances from sklearn.feature_extraction.text import TfidfVectorizer paired_cosine_distances( np.array([[1, 1], [0, 1], [0, 0], [1, 0]]), np.array([[1, 1], [0, 1], [0, 1], [0, 1]]) ) # Outputs: array([0.
