Evolutionary Computation in Data Mining

• Corporate Author: SpringerLink (Online service)
• Other Authors: Ghosh, Ashish (Editor), Jain, Lakhmi C. (Editor)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.
• Series: Studies in Fuzziness and Soft Computing, 163
• Subjects: Computer science.; Database management.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Computer Science.; Artificial Intelligence (incl. Robotics).; Appl.Mathematics/Computational Methods of Engineering.; Database Management.

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...

Table of Contents:

• Evolutionary Algorithms for Data Mining and Knowledge Discovery
• Strategies for Scaling Up Evolutionary Instance Reduction Algorithms for Data Mining
• GAP: Constructing and Selecting Features with Evolutionary Computing
• Multi-Agent Data Mining using Evolutionary Computing
• A Rule Extraction System with Class-Dependent Features
• Knowledge Discovery in Data Mining via an Evolutionary Algorithm
• Diversity and Neuro-Ensemble
• Unsupervised Niche Clustering: Discovering an Unknown Number of Clusters in Noisy Data Sets
• Evolutionary Computation in Intelligent Network Management
• Genetic Programming in Data Mining for Drug Discovery
• Microarray Data Mining with Evolutionary Computation
• An Evolutionary Modularized Data Mining Mechanism for Financial Distress Forecasts.