Changeset 7227:099f613e5927 in orange


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Timestamp:
02/02/11 19:23:07 (3 years ago)
Author:
miha <miha.stajdohar@…>
Branch:
default
Convert:
84b1f95cb10065abfe1e025ac1389492d20aa3d7
Message:
 
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1 edited

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  • orange/Orange/classification/svm/__init__.py

    r7219 r7227  
    88.. index:: Support Vector Machines Classification 
    99 
    10 Interface to the LibSVM library (LIBSVM : a library for support vector machines 
    11 (http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.ps.gz) 
     10Interface to the LibSVM library (a library for support vector machines 
     11- http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.ps.gz) 
    1212 
    1313.. note:: On some data-sets SVM can perform very badly. It is a known fact that 
     
    173173            (can be kernels.RBF (default), kernels.Linear, kernels.Polynomial,  
    174174            kernels.Sigmoid, kernels.Custom) 
    175         :type kernel_type: SVMLearner.Kernel 
     175        :type kernel_type: classification.kernels.Kernel 
    176176        :param degree: Kernel parameter (for Polynomial) (default 3) 
    177177        :type degree: int 
     
    182182        :type coef0: int 
    183183        :param kernelFunc: Function that will be called if `kernel_type` is 
    184             `Custom`. It must accept two `Orange.data.Example` arguments and 
     184            `Custom`. It must accept two `data.Example` arguments and 
    185185            return a float (the distance between the examples). 
    186186        :type kernelFunc: callable function 
     
    279279        cross validation. 
    280280         
    281         :param examples: ExampleTable on which to tune the parameters  
     281        :param examples: data.Table on which to tune the parameters  
    282282        :param parameters: if not set defaults to ["nu", "C", "gamma"] 
    283283        :param folds: number of folds used for cross validation 
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