Changeset 9900:795a819ca3bb in orange


Ignore:
Timestamp:
02/07/12 11:21:30 (2 years ago)
Author:
blaz <blaz.zupan@…>
Branch:
default
Message:

preliminary discretization structure (draft)

Files:
1 added
3 edited

Legend:

Unmodified
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  • Orange/feature/discretization.py

    r9878 r9900  
    1515    Discretization, \ 
    1616    Preprocessor_discretize 
    17  
    18  
    1917 
    2018def entropyDiscretization_wrapper(data): 
  • docs/reference/rst/Orange.data.rst

    r9891 r9900  
    1212    Orange.data.sample 
    1313    Orange.data.formats 
     14    Orange.data.discretization 
  • docs/reference/rst/Orange.feature.discretization.rst

    r9863 r9900  
    4949value according to the rule found by discretization. In this respect, the discretization behaves similar to 
    5050:class:`Orange.classification.Learner`. 
    51  
    52 Utility functions 
    53 ================= 
    54  
    55 Some functions and classes that can be used for 
    56 categorization of continuous features. Besides several general classes that 
    57 can help in this task, we also provide a function that may help in 
    58 entropy-based discretization (Fayyad & Irani), and a wrapper around classes for 
    59 categorization that can be used for learning. 
    60  
    61 .. autoclass:: Orange.feature.discretization.DiscretizedLearner_Class 
    62  
    63 .. autoclass:: DiscretizeTable 
    64  
    65 .. rubric:: Example 
    66  
    67 FIXME. A chapter on `feature subset selection <../ofb/o_fss.htm>`_ in Orange 
    68 for Beginners tutorial shows the use of DiscretizedLearner. Other 
    69 discretization classes from core Orange are listed in chapter on 
    70 `categorization <../ofb/o_categorization.htm>`_ of the same tutorial. 
    7151 
    7252Discretization Algorithms 
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