Heuristic and Optimization for Knowledge Discovery
Published on 1. July 2001
Book
Hardback
300 pages
978-1-930708-26-6 (ISBN)
Description
With the large amount of data stored by many organizations, capitalists have observed that this information is an intangible asset. Unfortunately, handling large databases is a very complex process and traditional learning techniques are expensive to use. Heuristic techniques provide much help in this arena, although little is known about heuristic techniques. Heuristic and Optimization for Knowledge Discovery addresses the foundation of this topic, as well as its practical uses, and aims to fill in the gap that exists in current literature.
More details
Language
English
Place of publication
Hershey
United States
Publishing group
IGI Global
Target group
College/higher education
Professional and scholarly
Illustrations
Illustrations
Weight
685 gr
ISBN-13
978-1-930708-26-6 (9781930708266)
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Schweitzer Classification
Content
Heuristic and Optimization for Knowledge Discovery; A Heuristic Algorithm for Feature Selection Based on Optimization Techniques; Cost-Sensitive Classification using Decision Trees, Boosting and MetaCost; Heuristic Search-Based Stacking of Classifiers; Designing Component-Based Heuristic Search Engines for Knowledge Discovery; Clustering Mixed Incomplete Data; Bayesian Learning; The Role of Sampling in Data Mining; The Gamma Test; Neural Networks; How to Train Multilayer Perceptrons Efficiently with Large Data; Cluster Analysis of Marketing Data Examining On-Line Shopping; Heuristics in Medical Data Mining; Understanding Credit Card Users Behaviour; Heuristic Knowledge Discovery for Archaeological Data Using Cultural Algorithms and Rough Sets