Title :
Genetic algorithms as a tool for restructuring feature space representations
Author :
Vafaie, Haleh ; De Jong, Kenneth
Author_Institution :
Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA
Abstract :
This paper describes an approach being explored to improve the usefulness of machine learning techniques to classify complex, real world data. The approach involves the use of genetic algorithms as a “front end” to a traditional tree induction system (ID3) in order to find the best feature set to be used by the induction system. This approach has been implemented and tested on difficult texture classification problems. The results are encouraging and indicate significant advantages of the presented approach
Keywords :
feature extraction; genetic algorithms; image classification; image texture; inference mechanisms; learning (artificial intelligence); ID3; feature space representations; genetic algorithms; image classification; image recognition; machine learning; texture classification problems; tree induction system; Algorithm design and analysis; Classification tree analysis; Computer science; Costs; Genetic algorithms; Image recognition; Machine learning; Manufacturing; Testing; Working environment noise;
Conference_Titel :
Tools with Artificial Intelligence, 1995. Proceedings., Seventh International Conference on
Conference_Location :
Herndon, VA
Print_ISBN :
0-8186-7312-5
DOI :
10.1109/TAI.1995.479372
