[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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