Constructive meta-level feature selection method based on method repositories

Hidenao Abe, Takahira Yamaguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Feature selection is one of key issues related with data preprocessing of classification task in a data mining process. Although many efforts have been done to improve typical feature selection algorithms (FSAs), such as filter methods and wrapper methods, it is hard for just one FSA to manage its performances to various datasets. To above problems, we propose another way to support feature selection procedure, constructing proper FSAs to each given dataset. Here is discussed constructive meta-level feature selection that re-constructs proper FSAs with a method repository every given datasets, de-composing representative FSAs into methods. After implementing the constructive meta-level feature selection system, we show how constructive meta-level feature selection goes well with 32 UCI common data sets, comparing with typical FSAs on their accuracies. As the result, our system shows the highest performance on accuracies and the availability to construct a proper FSA to each given data set automatically.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages70-80
Number of pages11
Volume3918 LNAI
Publication statusPublished - 2006
Event10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2006 - Singapore, Singapore
Duration: 2006 Apr 92006 Apr 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3918 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2006
CountrySingapore
CitySingapore
Period06/4/906/4/12

Fingerprint

Repository
Feature Selection
Feature extraction
Data Mining
Datasets
Data Preprocessing
Filter Method
Wrapper
Selection Procedures
Data mining
Availability
High Performance

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Abe, H., & Yamaguchi, T. (2006). Constructive meta-level feature selection method based on method repositories. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3918 LNAI, pp. 70-80). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3918 LNAI).

Constructive meta-level feature selection method based on method repositories. / Abe, Hidenao; Yamaguchi, Takahira.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3918 LNAI 2006. p. 70-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3918 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abe, H & Yamaguchi, T 2006, Constructive meta-level feature selection method based on method repositories. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3918 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3918 LNAI, pp. 70-80, 10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2006, Singapore, Singapore, 06/4/9.
Abe H, Yamaguchi T. Constructive meta-level feature selection method based on method repositories. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3918 LNAI. 2006. p. 70-80. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Abe, Hidenao ; Yamaguchi, Takahira. / Constructive meta-level feature selection method based on method repositories. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3918 LNAI 2006. pp. 70-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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