A system of rule extraction out of a complex hierarchical classifier is proposed in this paper.
There are several methods for rule extraction out of trained artificial neural networks (ANN's) …

Classification is an important field of data mining problems. Given a set of labeled training
examples the classification task constructs a classifier. A classifier is a global model which is …

This paper proposes a classification framework based on simple classifiers organized in a
tree‐like structure. It is observed that simple classifiers, even though they have high error …

Learning classi er systems are rule-based systems that exploit evolutionary c-putation and
reinforcement learning to solve di cult problems. They were-troduced in 1978 by John H …

This paper describes a method of extracting rules from trained neural network based on two-
level hierarchical evolutionary algorithm. Evolutionary algorithm on the lower level extracts …

Performance of hierarchical classifiers depends on two aspects–the performance of the
individual classifiers, and the design of the architecture. In this paper, we present a scheme …

An algorithm is presented to train a special kind of a local basis function classifier. The so-
called" rectangular basis function network"(RecBFN) consists of hidden units, each covering …

This paper describes a novel method of extracting rules from trained artificial neural
networks. The system which uses genetic algorithms to find an optimal path through the …

This work deals with the efficient discovery of valuable and nonobvious information from
large collections of data, using Computacional Intelligence tools. For this purpose, a. study …

A clustering genetic algorithm for extracting rules from multilayer perceptions trained in
classification problems ER Hruschka1 & NFF Ebecken2 1 Universidade Tuiuti do Paranci …