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train_matrix = rating_matrix.copy()
test_matrix = np.zeros(ratings_matrix.shape)
for i in xrange(rating_matrix.shape[0]):
rating_idx = np.random.choice(
rating_matrix[i, :].nonzero()[0],
train_matrix[i, rating_idx] = 0.0
test_matrix[i, rating_idx] = rating_matrix[i, rating_idx]
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