DocumentCode
2396411
Title
A comparison between fuzzy-ID3 and OFFSS-based fuzzy-ID3
Author
Hu, Guang-Ming ; Wang, Xi-Zhao
Author_Institution
Machine Learning Center, Hebei Univ., Baoding, China
Volume
7
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
4171
Abstract
In this paper, a method of combining fuzzy decision tree with optimal fuzzy-valued feature subset selection (OFFSS) is proposed. This algorithm can first select a feature subset from the entire feature space, and then constructs the fuzzy decision tree on the selected feature subset. This work conducts some experiments to compare the proposed algorithm with fuzzy-ID3. The experiment results show that fuzzy decision trees on feature subset are superior to that on entire feature space in terms of speed and accuracy for classification.
Keywords
decision trees; feature extraction; fuzzy set theory; learning (artificial intelligence); pattern classification; feature space; fuzzy ID3; fuzzy decision tree; machine learning; optimal fuzzy valued feature subset selection; pattern classification; Computer science; Data mining; Decision trees; Diversity reception; Frequency selective surfaces; Fuzzy sets; Machine learning; Machine learning algorithms; Mathematics; Samarium;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1384571
Filename
1384571
Link To Document