Ignore:
Timestamp:
07/01/13 12:28:13 (10 months ago)
Author:
Ales Erjavec <ales.erjavec@…>
Branch:
default
Message:

Added some basic documentation for the LIBLINEAR based classifiers.

File:
1 edited

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  • docs/reference/rst/Orange.classification.svm.rst

    r10696 r11605  
    6666subclasses. A down side is that they support only a linear kernel and 
    6767can not estimate probabilities. 
     68 
    6869    
    6970.. autoclass:: Orange.classification.svm.LinearSVMLearner 
    7071   :members: 
     72 
    7173    
    7274.. autoclass:: Orange.classification.svm.MultiClassSVMLearner 
    7375   :members: 
     76 
     77 
     78.. class:: LinearClassifier 
     79 
     80   The classifier returned by LIBLINEAR based learners. 
     81 
     82   .. attribute:: weights 
     83 
     84      A 2 dim table of computed feature weights of the classifier, 
     85      one for each one vs. rest underlying binary classifier (i.e. 
     86      ``classifier.weights[i]`` contains the i'th class vs. rest 
     87      binary classifier weights. If :attr:`bias` > 0 then the bias 
     88      weight term is appended as the last element of the weight 
     89      vector. 
     90 
     91   .. attribute:: bias 
     92 
     93      The bias parameter as passed to the learner. 
    7494    
    7595    
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