@inproceedings{c65c348659fe4c9fa9664d3e808ad30e,
title = "Logical rule extraction from data by maximum neural networks",
abstract = "In this paper, a new neural computing method to extract logical rules from the training data sets is proposed. Maximum neural networks are used to train the weight and the threshold of the multi-layered (feedforward) neural network (MLNN). The threshold and the weights of the MLNN are trained to be a logical function (AND/OR) with the multiple input. The maximum neural network constructs the logical function on the MLNN so that it is not necessary to extract rules from the trained MLNN. The proposed method was experimented for the classification problem, Monk's problem 1. Experimental results showed that the proposed method learned the correct rule in more than 40% success rate.",
author = "T. Saito and Y. Takefuji",
year = "1999",
month = jan,
day = "1",
doi = "10.1109/IPMM.1999.791477",
language = "English",
series = "Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "723--728",
editor = "Veiga, {Marcello M.} and Meech, {John A.} and Smith, {Michael H.} and LeClair, {Steven R.}",
booktitle = "Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999",
note = "2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999 ; Conference date: 10-07-1999 Through 15-07-1999",
}