silhouette_samples gives incorrect result from precomputed distance matrix with diagonal entries

Description

silhouette_samples gives incorrect result from precomputed distance matrix with diagonal entries.

When using silhouette_samples and metric=‘precomputed’, if the input distance matrix has non-zero values along the diagonal then the silhouette scores are incorrect.

Suggested Solution Before calculating the scores the diagonal entries of a precomputed distance matrix should be set to zero.

Steps/Code to Reproduce

Example:

import numpy as np
from sklearn.metrics.pairwise import pairwise_distances
from sklearn.metrics import silhouette_samples

dists = pairwise_distances(np.array([[0.2, 0.1, 0.12, 1.34, 1.11, 1.6]]).transpose())
diag_dists = np.diag(np.ones(6)) + dists

labels = [0,0,0,1,1,1]

print(silhouette_samples(diag_dists, labels, metric = 'precomputed'))

Expected Results

[0.92173913, 0.952, 0.95934959, 0.79583333, 0.62886598, 0.74315068]

Actual Results

[0.48695652, 0.552, 0.55284553, 0.37916667, 0.11340206, 0.40068493]

Versions

Darwin-17.7.0-x86_64-i386-64bit Python 3.6.4 |Anaconda, Inc.| (default, Jan 16 2018, 12:04:33) [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)] NumPy 1.15.1 SciPy 1.1.0 Scikit-Learn 0.20.0

[jnothman]

(Also, hi Stephen!)

[mathewphilipc]

If this is still in need of fixing, I’d like to take this on.