A Two-Phase Heuristic Construction of Feature Sets for Classification

Author

García-Torres, Miguel ; Ruiz, Roberto ; Batista, Belén Melián ; Pérez, José A Moreno ; Moreno-Vega, J. Marcos

Author_Institution

Escuela Politcnica Super., Univ. Pablo de Olavide, Sevilla, Spain

fYear

2011

fDate

7-9 Nov. 2011

Firstpage

1028

Lastpage

1031

Abstract

The aim of feature selection applied to a classification task is to find a minimal subset of features for being used in the classification. Some researches have focused their effort on selecting a useful set of attributes, others on selecting a relevant and not redundant set of attributes. We proposed a heuristic construction algorithm for selecting a useful and not redundant subset of features. The algorithm proposed belongs to the filter approach and make use of a correlation measure for the task.

Keywords

data mining; feature extraction; pattern classification; set theory; classification task; data mining; feature selection; feature sets; filter approach; two-phase heuristic construction algorithm; Algorithm design and analysis; Approximation algorithms; Databases; Heuristic algorithms; Machine learning; Markov processes; Redundancy; Feature selection; classification; data mining; feature ranking;

fLanguage

English

Publisher

ieee

Conference_Titel

Tools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on

Conference_Location

Boca Raton, FL

ISSN

1082-3409

Print_ISBN

978-1-4577-2068-0

Electronic_ISBN

1082-3409

Type

conf

DOI

10.1109/ICTAI.2011.175

Filename

6103466