Fundations of Decision Rule Induction: Covering Algorithms

Automatically Evolving Rule Induction Algorithms

Research in the rule induction algorithm field produced many algorithms in the last 30 years. However, these algorithms are usually obtained from a few basic rule induction algorithms that have been often changed to produce better ones. Having these basic algorithms and their components in mind, this work proposes the use of Grammar-based Genetic Programming (GGP) to automatically evolve rule i...

Genetic Algorithms and Poker Rule Induction

This thesis is intended to be an experiment on Genetic Algorithms (GAs). The general algorithm is applied to a specific dataset of poker hands. Its performance in detecting the rules of poker games is then evaluated in different measures and conditions. Based on the performance of the algorithm, further understanding of the data can be obtained.

Creating Rule Ensembles from Automatically-Evolved Rule Induction Algorithms

Ensembles are a set of classification models that, when combined, produce better predictions than when used by themselves. This chapter proposes a new evolutionary algorithm-based method for creating an ensemble of rule sets consisting of two stages. First, an evolutionary algorithm (more precisely, a genetic programming algorithm) is used to automatically create complete rule induction algorit...

Reusable components in decision tree induction algorithms

We propose a generic decision tree framework that supports reusable components design. The proposed generic decision tree framework consists of several sub-problems which were recognized by analyzing well-known decision tree induction algorithms, namely ID3, C4.5, CART, CHAID, QUEST, GUIDE, CRUISE, and CTREE. We identified reusable components in these algorithms as well as in several of their p...

Evolutionary Algorithms in Decision Tree Induction