[Scipy-svn] r4188 - trunk/scipy/cluster
scipy-svn@scip...
scipy-svn@scip...
Sun Apr 27 07:52:46 CDT 2008
Author: damian.eads
Date: 2008-04-27 07:52:45 -0500 (Sun, 27 Apr 2008)
New Revision: 4188
Modified:
trunk/scipy/cluster/vq.py
Log:
Tightening up the language of vq's module summary.
Modified: trunk/scipy/cluster/vq.py
===================================================================
--- trunk/scipy/cluster/vq.py 2008-04-27 12:48:25 UTC (rev 4187)
+++ trunk/scipy/cluster/vq.py 2008-04-27 12:52:45 UTC (rev 4188)
@@ -10,11 +10,12 @@
clusters. An observation vector is classified with the cluster
number or centroid index of the centroid closest to it.
- Most variants of k-means try to minimize distortion, which is
- defined as the sum of the distances between each observation and
- its dominating centroid. A vector belongs to a cluster i if it is
- closer to centroid i than the other centroids. Each step of the
- k-means algorithm refines the choices of centroids to reduce
+ A vector v belongs to cluster i if it is closer to centroid i than
+ the other centroids. If v belongs to i, we say centroid i is the
+ dominating centroid of v. Most variants of k-means try to minimize
+ distortion, which is defined as the sum of the distances between
+ each observation vector and its dominating centroid. Each step of
+ the k-means algorithm refines the choices of centroids to reduce
distortion. The change in distortion is often used as a stopping
criterion: when the change is lower than a threshold, the k-means
algorithm is not making progress and terminates.
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