Enhancing classification performance using attribute-oriented functionally expanded data

Enhancing classification performance using attribute-oriented functionally expanded data

João Roberto Bertini Junior, Maria do Carmo Nicoletti

ARTIGO

Inglês

Agradecimentos: The authors thank CAPES and CNPq for the research grant received.

There are many data pre-processing techniques that aim at enhancing the quality of classifiers induced by machine learning algorithms. Functional expansions (FE) are one of such techniques, which has been originally proposed to aid neural network based cl

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ

COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES

Fechado

Enhancing classification performance using attribute-oriented functionally expanded data

João Roberto Bertini Junior, Maria do Carmo Nicoletti


										

Enhancing classification performance using attribute-oriented functionally expanded data

João Roberto Bertini Junior, Maria do Carmo Nicoletti

    Fontes

    Pattern recognition letters

    Vol. 89 (Apr., 2017), p. 39-45