sklearn.metrics.pairwise.manhattan_distances(X, Y=None, sum_over_features=True, size_threshold=None)
[source]
Compute the L1 distances between the vectors in X and Y.
With sum_over_features equal to False it returns the componentwise distances.
Read more in the User Guide.
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>>> from sklearn.metrics.pairwise import manhattan_distances >>> manhattan_distances([[3]], [[3]]) array([[0.]]) >>> manhattan_distances([[3]], [[2]]) array([[1.]]) >>> manhattan_distances([[2]], [[3]]) array([[1.]]) >>> manhattan_distances([[1, 2], [3, 4]], [[1, 2], [0, 3]]) array([[0., 2.], [4., 4.]]) >>> import numpy as np >>> X = np.ones((1, 2)) >>> y = np.full((2, 2), 2.) >>> manhattan_distances(X, y, sum_over_features=False) array([[1., 1.], [1., 1.]])
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Licensed under the 3-clause BSD License.
http://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.manhattan_distances.html