Imputing Missing Class Labels Using k-Nearest Neighbors Preliminaries import numpy as np from sklearn.neighbors import KNeighborsClassifier Create Feature Matrix X = np.array([[0, 2.10, 1.45], [1, 1.18, 1.33], [0, 1.22, 1.27], [1, -0.21, -1.19]]) Create Feature Matrix With Missing Values X_with_nan = np.array([[np.nan, 0.87, 1.31], [np.nan, -0.67, -0.22]]) Train k-Nearest Neighbor Classifier clf = KNeighborsClassifier(3, weights=’distance’) … Continue reading Machine Learning for Beginners in Python: Imputing Missing Class Labels Using k-Nearest Neighbors