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

Legend:

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  • Orange/classification/logreg.py

    r11459 r11605  
    10271027 
    10281028class LibLinearLogRegLearner(Orange.core.LinearLearner): 
    1029     """A logistic regression learner from `LIBLINEAR`_. 
     1029    """ 
     1030    A logistic regression learner from `LIBLINEAR`_. 
    10301031 
    10311032    Supports L2 regularized learning. 
    10321033 
    10331034    .. _`LIBLINEAR`: http://www.csie.ntu.edu.tw/~cjlin/liblinear/ 
     1035 
     1036    .. note:: 
     1037        Unlike :class:`LogRegLearner` this one supports multi-class 
     1038        classification using one vs. rest strategy. 
    10341039 
    10351040    """ 
     
    10851090 
    10861091    def __call__(self, data, weight_id=None): 
     1092        """ 
     1093        Return a classifier trained on the `data` (`weight_id` is ignored). 
     1094 
     1095        :param Orange.data.Table data: 
     1096            Training data set. 
     1097        :param int weight_id: 
     1098            Ignored. 
     1099        :rval: Orange.core.LinearClassifier 
     1100 
     1101        .. note:: 
     1102            The :class:`Orange.core.LinearClassifier` is same class as 
     1103            :class:`Orange.classification.svm.LinearClassifier`. 
     1104 
     1105        """ 
    10871106        if not isinstance(data.domain.class_var, Orange.feature.Discrete): 
    10881107            raise TypeError("Can only learn a discrete class.") 
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