Changeset 7590:d80a21d0c013 in orange


Ignore:
Timestamp:
02/05/11 00:27:58 (3 years ago)
Author:
blaz <blaz.zupan@…>
Branch:
default
Convert:
2590d561e0df630edf4364364a6fe6707b7c6456
Message:

changed some section titles and their markup

File:
1 edited

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

    r7410 r7590  
    33.. index:: classification, support vector machines (SVM) 
    44 
    5 ======================= 
    6 Support Vector Machines 
    7 ======================= 
     5*********************** 
     6Support vector machines 
     7*********************** 
    88 
    99A collection of classes that wrap the  
    10 `LibSVM library <http://www.csie.ntu.edu.tw/~cjlin/libsvm/>`_ (a library for  
    11 `support vector machines <http://en.wikipedia.org/wiki/Support_vector_machine>`_) 
     10`LibSVM library <http://www.csie.ntu.edu.tw/~cjlin/libsvm/>`_, a library for  
     11`support vector machines <http://en.wikipedia.org/wiki/Support_vector_machine>`_ (SVM). 
     12In this way SVM learners from LibSVM behave like ordinary Orange learners and can 
     13be used as Python objects in training, classification and evaluation tasks. The 
     14implementation supports the implementation of Python-based kernels, that can be 
     15plugged-in into LibSVM implementations. 
    1216 
    1317.. note:: On some data-sets SVM can perform very poorly. SVM can be very  
     
    1721          and use the :obj:`SVMLearnerEasy` class which does this automatically 
    1822          (it is similar to the `svm-easy.py`_ script in the LibSVM distribution). 
     23           
     24SVM learners 
     25============ 
    1926 
    2027.. autoclass:: Orange.classification.svm.SVMLearner 
     
    2734   :members: 
    2835    
    29 Usefull functions 
    30 ================= 
     36Utility functions 
     37----------------- 
    3138 
    3239.. automethod:: Orange.classification.svm.maxNu 
     
    3643.. automethod:: Orange.classification.svm.tableToSVMFormat 
    3744 
    38 SVM derived feature weights 
    39 =========================== 
     45SVM-derived feature weights 
     46--------------------------- 
    4047 
    4148.. autoclass:: Orange.classification.svm.MeasureAttribute_SVMWeights 
     
    4451.. _kernel-wrapper: 
    4552 
     53 
     54Kernel wrappers 
    4655=============== 
    47 Kernel Wrappers 
    48 =============== 
    4956 
    5057.. autoclass:: Orange.classification.svm.kernels.KernelWrapper 
     
    7986.. literalinclude:: code/svm-custom-kernel.py 
    8087 
    81 ======================================= 
    82 SVM-Based Recursive Feature Elimination 
     88 
     89 
     90SVM-based recursive feature elimination 
    8391======================================= 
    8492 
     
    93101.. _iris.tab: code/iris.tab 
    94102.. _vehicle.tab: code/vehicle.tab 
    95  
    96 References 
    97 ==========  
    98  
    99 C.-W. Hsu, C.-C. Chang, C.-J. Lin. A practical guide to support vector  
    100 classification 
    101  
    102103""" 
     104 
    103105import math 
    104106 
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