Alexandre Abraham AlexandreAbraham
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| from math import ceil | |
| from functools import partial | |
| from matplotlib import pyplot as plt | |
| from cycler import cycler | |
| import numpy as np | |
| from decimal import Context | |
| plt.rcParams['figure.constrained_layout.use'] = True | |
| ctx = Context(prec=20) |
AlexandreAbraham
/ unsupervised_alt.py
Last active
February 5, 2023 23:00
These are two implementations of the silhouette score. They are compatible with the scikit learn implementation but offers different drawbacks in term of complexity and memory usage. The slow version needs no memory but is painfully slow and should, I think, not be used. The second one is based on a block strategy: distance between samples and c…
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| """ Unsupervised evaluation metrics. """ | |
| # License: BSD Style. | |
| from itertools import combinations | |
| import numpy as np | |
| from sklearn.utils import check_random_state | |
| from sklearn.metrics.pairwise import distance_metrics | |
| from sklearn.metrics.pairwise import pairwise_distances |