Title :
Iterative rule simplification for noise tolerant inductive learning
Author :
Pachowicz, Peter W. ; Bala, Jerzy ; Zhang, Jianping
Author_Institution :
Center for Artificial Intelligence, George Mason Univ., Fairfax, VA, USA
Abstract :
An iterative noise reduction learning algorithm is presented in which rules are learned in two phases. The first phase improves the quality of training data through a concept-driven closed-loop filtration process. In the second phase, classification rules are relearned from the filtered training data set
Keywords :
knowledge acquisition; learning (artificial intelligence); classification rules; concept-driven closed-loop filtration process; iterative noise reduction learning algorithm; noise tolerant inductive learning; training data; Algorithm design and analysis; Artificial intelligence; Computer science; Filtration; Iterative algorithms; Learning systems; Noise reduction; Phase noise; System testing; Training data;
Conference_Titel :
Tools with Artificial Intelligence, 1992. TAI '92, Proceedings., Fourth International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
0-8186-2905-3
DOI :
10.1109/TAI.1992.246447
