학술논문
Feature selection based on information theory, consistency and separability indices
Document Type
Conference
Author
Source
Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02. Neural information processing Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on. 4:1951-1955 vol.4 2002
Subject
Language
Abstract
Two new feature selection methods are introduced, the first based on separability criterion, the second on a consistency index that includes interactions between the selected subsets of features. Comparison of accuracy was made against information-theory based selection methods on several datasets training neurofuzzy and nearest neighbor methods on various subsets of selected features. Methods based on separability seem to be most promising.