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 …

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) …

Contrary to much of the research in machine learning where there is a concentration on
problems with relatively small volume of data, one of the main challenges of the today's data …

This report describes in a comprehensive manner the various types of classification
algorithms that already exist. I will mainly be discussing and comparing in detail the major 7 …

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 …

There are many learning algorithms available in the field of pattern classification and people
are still discovering new algorithms that they hope will work better. Any new learning …

In the paper we discuss a new approach for learning classification rules from examples. We
sketch out the algorithm JoJo and its extension to a four step procedure which can be used …

This paper introduces a new method for learning algorithm evaluation and selection, with
empirical results based on classification. The empirical study has been conducted among 8 …

Abstract Top Down Induction of Decision Trees (TDIDT) is the most commonly used method
of constructing a model from a dataset in the form of classification rules to classify previously …

We propose a method for learning rule-based classifiers that can be seen as a compromise
between a complete enumeration of the hypothesis space and heuristic strategies to search …