Andrei Zaitcev AndreiZaitcev
AndreiZaitcev
/ canopy.py
Created
April 10, 2016 12:41
— forked from gdbassett/canopy.py
Efficient python implementation of canopy clustering. (A method for efficiently generating centroids and clusters, most commonly as input to a more robust clustering algorithm.)
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| from sklearn.metrics.pairwise import pairwise_distances | |
| import numpy as np | |
| # X shoudl be a numpy matrix, very likely sparse matrix: http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.sparse.csr_matrix.html#scipy.sparse.csr_matrix | |
| # T1 > T2 for overlapping clusters | |
| # T1 = Distance to centroid point to not include in other clusters | |
| # T2 = Distance to centroid point to include in cluster | |
| # T1 > T2 for overlapping clusters | |
| # T1 < T2 will have points which reside in no clusters | |
| # T1 == T2 will cause all points to reside in mutually exclusive clusters |