Changeset 9495:57857a5d0e0b in orange


Ignore:
Timestamp:
09/02/11 07:50:09 (3 years ago)
Author:
wencanluo <wencanluo@…>
Branch:
default
Convert:
ad34b0f7f0ecd7be589bea84f33b1f1e3444b976
Message:

Fixed some type errors in the documents

Location:
orange/Orange/multilabel
Files:
2 edited

Legend:

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  • orange/Orange/multilabel/brknn.py

    r9477 r9495  
    1010in conjunction with the kNN algorithm. It also implements two extensions of BR-kNN.  
    1111For more information, see E. Spyromitros, G. Tsoumakas, I. Vlahavas,  
    12 'An Empirical Study of Lazy Multilabel Classification Algorithms <http://mlkd.csd.auth.gr/multilabel.html>',  
     12`An Empirical Study of Lazy Multilabel Classification Algorithms <http://mlkd.csd.auth.gr/multilabel.html>`_,  
    1313Proc. 5th Hellenic Conference on Artificial Intelligence (SETN 2008), Springer, Syros, Greece, 2008.   
    1414 
  • orange/Orange/multilabel/mlknn.py

    r9477 r9495  
    88ML-kNN Classification is a kind of adaptation method for multi-label classification.  
    99It is an adaptation of the kNN lazy learning algorithm for multi-label data.  
    10 In essence, ML-kNN uses the kNN algorithm independently for each label :math:'l':  
     10In essence, ML-kNN uses the kNN algorithm independently for each label :math:`l`. 
    1111It finds the k nearest examples to the test instance and considers those that are  
    12 labelled at least with :math:'l' as positive and the rest as negative.  
     12labelled at least with :math:`l` as positive and the rest as negative.  
    1313Actually this method follows the paradigm of Binary Relevance (BR). What mainly  
    1414differentiates this method from BR is the use of prior probabilities. ML-kNN has also 
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