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than as an average. This is much more relevant when you have many labels, rather than just two. from sklearn.preprocessing import LabelEncoder from sklearn.metrics import accuracy_score, confusion_matrix import numpy as np label_encoder = LabelEncoder() label_encoder.fit(unique_labels) def