Changeset 7179:8d575f971184 in orange


Ignore:
Timestamp:
01/31/11 12:48:01 (3 years ago)
Author:
blaz <blaz.zupan@…>
Branch:
default
Convert:
083c861cc92d29e2998a75e117c518afc9bbe3e1
Message:

misc

File:
1 edited

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  • orange/Orange/cluster/__init__.py

    r7107 r7179  
    11""" 
    22 
    3 .. index:: clutering 
     3.. index:: clustering 
     4 
     5Everything about clustering, including agglomerative and hierarchical clustering. 
    46 
    57================== 
     
    447449class KMeans: 
    448450    """ 
    449     K-means clustering algorithm: 
     451    Implements a k-means clustering algorithm: 
    450452 
    451453    #. Choose the number of clusters, k. 
     
    457459       met (e.g., the cluster assignment has not changed). 
    458460 
    459     The main advantage of the algorithm is simplicity and low memory   
     461    The main advantages of this algorithm are simplicity and low memory   
    460462    requirements. The principal disadvantage is the dependence of results  
    461463    on the selection of initial set of centroids. 
     
    475477                 outer_callback = None): 
    476478        """ 
    477         :param data: Instances to be clustered. If not None, clustering will be executed immediately after initialization unless initialize_only is set to True. 
     479        :param data: Data instances to be clustered. If not None, clustering will be executed immediately after initialization unless initialize_only=True. 
    478480        :type data: :class:`orange.ExampleTable` or None 
    479481        :param centroids: either specify a number of clusters or provide a list of examples that will serve as clustering centroids. 
     
    516518         
    517519    def __call__(self, data = None): 
    518         """ Runs with optional new data. """ 
     520        """Runs the k-means clustering algorithm, with optional new data.""" 
    519521        if data: 
    520522            self.data = data 
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