Evolutionary Computation in Data Mining

✍ Scribed by Ashish Ghosh (auth.), Dr. Ashish Ghosh, Prof. Lakhmi C. Jain (eds.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2005
• Tongue: English
• Leaves: 278
• Series: Studies in Fuzziness and Soft Computing 163
• Edition: 1
• Category: Library

✦ Synopsis

This carefully edited book reflects and advances the state of the art in the area of Data Mining and Knowledge Discovery with Evolutionary Algorithms. It emphasizes the utility of different evolutionary computing tools to various facets of knowledge discovery from databases, ranging from theoretical analysis to real-life applications. "Evolutionary Computation in Data Mining" provides a balanced mixture of theory, algorithms and applications in a cohesive manner, and demonstrates how the different tools of evolutionary computation can be used for solving real-life problems in data mining and bioinformatics.

✦ Table of Contents

Evolutionary Algorithms for Data Mining and Knowledge Discovery....Pages 1-20
Strategies for Scaling Up Evolutionary Instance Reduction Algorithms for Data Mining....Pages 21-39
GAP: Constructing and Selecting Features with Evolutionary Computing....Pages 41-56
Multi-Agent Data Mining using Evolutionary Computing....Pages 57-78
A Rule Extraction System with Class-Dependent Features....Pages 79-99
Knowledge Discovery in Data Mining via an Evolutionary Algorithm....Pages 101-123
Diversity and Neuro-Ensemble....Pages 125-156
Unsupervised Niche Clustering: Discovering an Unknown Number of Clusters in Noisy Data Sets....Pages 157-188
Evolutionary Computation in Intelligent Network Management....Pages 189-210
Genetic Programming in Data Mining for Drug Discovery....Pages 211-235
Microarray Data Mining with Evolutionary Computation....Pages 237-248
An Evolutionary Modularized Data Mining Mechanism for Financial Distress Forecasts....Pages 249-263

✦ Subjects

Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics); Database Management