Changeset 7525:23e12cee5ae8 in orange


Ignore:
Timestamp:
02/04/11 20:39:41 (3 years ago)
Author:
blaz <blaz.zupan@…>
Branch:
default
Convert:
abac257dccf85fa144ffefa9faddd237c0bb5904
Message:

split btw kmans and hierarchical now complete

Location:
orange/Orange/clustering
Files:
3 edited

Legend:

Unmodified
Added
Removed
  • orange/Orange/clustering/__init__.py

    r7503 r7525  
    11""" 
    2  
    32.. index:: clustering 
    43 
    54Everything about clustering, including agglomerative and hierarchical clustering. 
    6  
    75 
    86================ 
     
    2018      :param n: katero fibonacijevo stevilo zelis 
    2119      :type n: integer 
    22     
    23  
    24 .. autoclass:: Orange.clustering.HierarchicalCluster 
    25    :members: 
    26    :show-inheritance: 
    27    :undoc-members: 
    28  
    29 .. autoclass:: Orange.clustering.HierarchicalClusterList 
    30    :members: 
    31    :show-inheritance: 
    32    :undoc-members: 
    33  
    34 .. autoclass:: Orange.clustering.HierarchicalClustering 
    35    :members: 
    36    :show-inheritance: 
    37    :undoc-members: 
    38  
    39  
    40  
    4120""" 
    4221 
  • orange/Orange/clustering/hierarchical.py

    r7503 r7525  
    11""" 
    2 ======================= 
    3 Hierarchical Clustering 
    4 ======================= 
     2*********************** 
     3Hierarchical clustering 
     4*********************** 
    55 
    66.. index:: 
     
    1212 
    1313An example. 
     14 
     15.. automethod:: Orange.clustering.hierarchical.clustering 
     16 
    1417""" 
    1518 
    1619import orange 
    1720 
    18 # hierarhical clustering 
    19  
    2021def clustering(data, 
    21                            distanceConstructor=orange.ExamplesDistanceConstructor_Euclidean, 
    22                            linkage=orange.HierarchicalClustering.Average, 
    23                            order=False, 
    24                            progressCallback=None): 
     22               distanceConstructor=orange.ExamplesDistanceConstructor_Euclidean, 
     23               linkage=orange.HierarchicalClustering.Average, 
     24               order=False, 
     25               progressCallback=None): 
    2526    """Return a hierarhical clustering of the data set.""" 
    2627    distance = distanceConstructor(data) 
  • orange/Orange/clustering/kmeans.py

    r7503 r7525  
    11""" 
    2 ================== 
    3 k-Means clustering 
    4 ================== 
     2****************** 
     3K-means clustering 
     4****************** 
    55 
    66.. index:: 
     
    1515======== 
    1616 
    17 The following code runs k-means clustering and prints out the cluster indexes 
     17XThe following code runs k-means clustering and prints out the cluster indexes 
    1818for the last 10 data instances (`kmeans-run.py`_, uses `iris.tab`_): 
    1919 
     
    6767.. automethod:: Orange.clustering.kmeans.init_diversity 
    6868 
    69 .. automethod:: Orange.clustering.kmeans.init_hclustering 
    70  
    71 .. automethod:: Orange.clustering.kmeans.data_center 
     69.. autoclass:: Orange.clustering.kmeans.init_hclustering 
     70   :members: 
    7271 
    7372.. automethod:: Orange.clustering.kmeans.data_center 
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