MEKA: A multi-label/multi-target extension to WEKA

Jesse Read, Peter Reutemann, Bernhard Pfahringer, Geoff Holmes

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

142 Sitaatiot (Scopus)
56 Lataukset (Pure)

Abstrakti

Multi-label classification has rapidly attracted interest in the machine learning literature, and there are now a large number and considerable variety of methods for this type of learning. We present MEKA: an open-source Java framework based on the well-known WEKA library. MEKA provides interfaces to facilitate practical application, and a wealth of multi-label classifiers, evaluation metrics, and tools for multi-label experiments and development. It supports multi-label and multi-target data, including in incremental and semi-supervised contexts.

AlkuperäiskieliEnglanti
Artikkeli21
Sivut1-5
JulkaisuJournal of Machine Learning Research
Vuosikerta17
TilaJulkaistu - 1 helmikuuta 2016
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

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