Changeset 5029:b3ec919c2bc6 in orange


Ignore:
Timestamp:
07/30/08 12:23:23 (6 years ago)
Author:
ales_erjavec <ales.erjavec@…>
Branch:
default
Convert:
27d0b06f35cb6a9a1a57989e7396997b5beef6d8
Message:

-fixed constant names

File:
1 edited

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  • orange/doc/modules/orngSVM.htm

    r3676 r5029  
    1616<dl class=arguments> 
    1717  <dt>svm_type</dt> 
    18   <dd>Defines the type of SVM (can be SVMLearner.C_SVC (default), SVMLearner.NU_SVC, SVMLearner.ONE_CLASS, SVMLearner.EPSILON_SVR, SVMLearner.NU_SVR)</dd> 
     18  <dd>Defines the type of SVM (can be SVMLearner.C_SVC (default), SVMLearner.Nu_SVC, SVMLearner.OneClass, SVMLearner.Epsilon_SVR, SVMLearner.Nu_SVR)</dd> 
    1919  <dt>kernel_type</dt> 
    20   <dd>Defines the type of a kernel to use for learning (can be SVMLearner.RBF (default), SVMLearner.LINEAR, SVMLearner.POLY, SVMLearner.SIGMOID, SVMLearner.CUSTOM)</dd> 
     20  <dd>Defines the type of a kernel to use for learning (can be SVMLearner.RBF (default), SVMLearner.Linear, SVMLearner.Polynomial, SVMLearner.Sigmoid, SVMLearner.Custom)</dd> 
    2121  <dt>degree</dt> 
    22   <dd>Kernel parameter (POLY) (default 3)</dd> 
     22  <dd>Kernel parameter (Polynomial) (default 3)</dd> 
    2323  <dt>gamma</dt> 
    24   <dd>Kernel parameter (POLY/RBF/SIGMOID) (default 1/number_of_examples)</dd> 
     24  <dd>Kernel parameter (Polynomial/RBF/Sigmoid) (default 1/number_of_examples)</dd> 
    2525  <dt>coef0</dt> 
    26   <dd>Kernel parameter (POLY/SIGMOID) (default 0)</dd> 
     26  <dd>Kernel parameter (Polynomial/Sigmoid) (default 0)</dd> 
    2727  <dt>kernelFunc</dt> 
    28   <dd>Function that will be called if <code>kernel_type</code> is SVMLearner.CUSTOM. It must accept two orange.Example arguments and return a float.</dd> 
     28  <dd>Function that will be called if <code>kernel_type</code> is SVMLearner.Custom. It must accept two orange.Example arguments and return a float.</dd> 
    2929  <dt>C</dt> 
    30   <dd>C parameter for C_SVC, EPSILON_SVR, NU_SVR</dd> 
     30  <dd>C parameter for C_SVC, Epsilon_SVR, Nu_SVR</dd> 
    3131  <dt>nu</dt> 
    32   <dd>Nu parameter for NU_SVC, NU_SVR and ONE_CLASS (default 0.5)</dd> 
     32  <dd>Nu parameter for Nu_SVC, Nu_SVR and OneClass (default 0.5)</dd> 
    3333  <dt>p</dt> 
    34   <dd>Epsilon in loss-function for EPSILON_SVR</dd> 
     34  <dd>Epsilon in loss-function for Epsilon_SVR</dd> 
    3535  <dt>cache_size</dt> 
    3636  <dd>Cache memory size in MB (default 100)</dd> 
     
    113113l1=orngSVM.SVMLearner() 
    114114l1.kernelFunc=orngSVM.RBFKernelWrapper(orange.ExamplesDistanceConstructor_Euclidean(data), gamma=0.5) 
    115 l1.kernel_type=orange.SVMLearner.CUSTOM 
     115l1.kernel_type=orange.SVMLearner.Custom 
    116116l1.probability=True 
    117117c1=l1(data) 
     
    120120l2=orngSVM.SVMLearner() 
    121121l2.kernelFunc=orngSVM.RBFKernelWrapper(orange.ExamplesDistanceConstructor_Hamming(data), gamma=0.5) 
    122 l2.kernel_type=orange.SVMLearner.CUSTOM 
     122l2.kernel_type=orange.SVMLearner.Custom 
    123123l2.probability=True 
    124124c2=l2(data) 
     
    127127l3=orngSVM.SVMLearner() 
    128128l3.kernelFunc=orngSVM.CompositeKernelWrapper(orngSVM.RBFKernelWrapper(orange.ExamplesDistanceConstructor_Euclidean(data), gamma=0.5),orngSVM.RBFKernelWrapper(orange.ExamplesDistanceConstructor_Hamming(data), gamma=0.5), l=0.5) 
    129 l3.kernel_type=orange.SVMLearner.CUSTOM 
     129l3.kernel_type=orange.SVMLearner.Custom 
    130130l3.probability=True 
    131131c3=l1(data) 
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