Title :
Evaluation and ordering of rules extracted from feedforward networks
Author :
Taha, Ismail ; Ghosh, Joydeep
Author_Institution :
Lab. of Artificial Neural Syst., Texas Univ., Austin, TX, USA
Abstract :
Rules extracted from trained feedforward networks can be used for explanation, validation, and cross-referencing of network output decisions. This paper introduces a rule evaluation and ordering mechanism that orders rules extracted from feedforward networks based on three performance measures. Detailed experiments using three rule extraction techniques as applied to the Wisconsin breast cancer database, illustrate the power of the proposed methods. Moreover, a method of integrating the output decisions of both the extracted rule-based system and the corresponding trained network is proposed. The integrated system provides further improvements
Keywords :
backpropagation; feedforward neural nets; inference mechanisms; knowledge based systems; medical expert systems; Wisconsin breast cancer database; backpropagation; feedforward neural networks; inference engine; rule evaluation; rule extraction; rule ordering; rule-based system; Breast cancer; Contracts; Databases; Interference; Knowledge acquisition; Knowledge based systems; Laboratories; Message-oriented middleware; Power engineering computing; Writing;
Conference_Titel :
Neural Networks,1997., International Conference on
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-4122-8
DOI :
10.1109/ICNN.1997.611703