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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1384571
