| class Clustering: | |
| def k_means_clustering(self, n, s=1.0): | |
| """ | |
| This method performs the K-means clustering algorithm on the data for n iterations. This involves updating the | |
| centroids using the mean-shift heuristic n-times and reassigning the patterns to their closest centroids. | |
| :param n: number of iterations to complete | |
| :param s: the scaling factor to use when updating the centroids | |
| pick on which has a better solution (according to some measure of cluster quality) | |
| """ | |
| for i in range(n): | |
| self.assign_patterns() | |
| self.update_centroids(s) |
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