FEATURE SELECTION METHODS BASED ON MUTUAL INFORMATION FOR CLASSIFYING HETEROGENEOUS FEATURES

FEATURE SELECTION METHODS BASED ON MUTUAL INFORMATION FOR CLASSIFYING HETEROGENEOUS FEATURES

Datasets with heterogeneous features can affect feature selection results that are not appropriate because it is difficult to evaluate heterogeneous features concurrently. Feature transformation (FT) is another way to handle heterogeneous features subset selection. The results of transformation from...

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Bibliographic Details
Main Authors: Ratri Enggar Pawening, Tio Darmawan, Rizqa Raaiqa Bintana, Agus Zainal Arifin, Darlis Herumurti
Format: Article
Language:English
Published: Universitas Indonesia 2016-06-01
Series:Jurnal Ilmu Komputer dan Informasi
Subjects:
Feature selection, Heterogeneous features, Joint mutual information maximation, Support vector machine, Unsupervised feature transformation
Online Access:http://jiki.cs.ui.ac.id/index.php/jiki/article/view/384

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http://jiki.cs.ui.ac.id/index.php/jiki/article/view/384

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