Changeset 7179:8d575f971184 in orange

Timestamp:

01/31/11 12:48:01 (2 years ago)

Author:

blaz <blaz.zupan@…>

Branch:

default

Convert:

083c861cc92d29e2998a75e117c518afc9bbe3e1

Message:

misc

File:

• orange/Orange/cluster/__init__.py (modified) (5 diffs)

orange/Orange/cluster/__init__.py

@@ -1 +1 @@
 """
 
-.. index:: clutering
+.. index:: clustering
+
+Everything about clustering, including agglomerative and hierarchical clustering.
 
 ==================
@@ -447 +449 @@
 class KMeans:
     """
-    K-means clustering algorithm:
+    Implements a k-means clustering algorithm:
 
     #. Choose the number of clusters, k.
@@ -457 +459 @@
        met (e.g., the cluster assignment has not changed).
 
-    The main advantage of the algorithm is simplicity and low memory  
+    The main advantages of this algorithm are simplicity and low memory  
     requirements. The principal disadvantage is the dependence of results 
     on the selection of initial set of centroids.
@@ -475 +477 @@
                  outer_callback = None):
         """
-        :param data: Instances to be clustered. If not None, clustering will be executed immediately after initialization unless initialize_only is set to True.
+        :param data: Data instances to be clustered. If not None, clustering will be executed immediately after initialization unless initialize_only=True.
         :type data: :class:`orange.ExampleTable` or None
         :param centroids: either specify a number of clusters or provide a list of examples that will serve as clustering centroids.
@@ -516 +518 @@
         
     def __call__(self, data = None):
-        """ Runs with optional new data. """
+        """Runs the k-means clustering algorithm, with optional new data."""
         if data:
             self.data = data