Changeset 9495:57857a5d0e0b in orange
- 09/02/11 07:50:09 (2 years ago)
- 2 edited
r9477 r9495 10 10 in conjunction with the kNN algorithm. It also implements two extensions of BR-kNN. 11 11 For 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 , 13 13 Proc. 5th Hellenic Conference on Artificial Intelligence (SETN 2008), Springer, Syros, Greece, 2008. 14 14
r9477 r9495 8 8 ML-kNN Classification is a kind of adaptation method for multi-label classification. 9 9 It 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': 10 In essence, ML-kNN uses the kNN algorithm independently for each label :math: 11 11 It 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. 12 labelled at least with :math: as positive and the rest as negative. 13 13 Actually this method follows the paradigm of Binary Relevance (BR). What mainly 14 14 differentiates this method from BR is the use of prior probabilities. ML-kNN has also
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