Join Books.org — it's free

Computer Science & Combinatorics, Programming - General & Miscellaneous, Mathematical Programming & Operations Research
Heuristic and Optimization for Knowledge Discovery by Ruhul Sarker, Hussein Abbass, Charles Newton — book cover

Heuristic and Optimization for Knowledge Discovery

by Ruhul Sarker, Hussein Abbass, Charles Newton
Write a review
Log in to track your reading progress.

Overview

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.

Reviews

There are no reviews yet. Log in to write one.

Editorials

From The Critics

Focusing on searching, optimization, statistics, data mining, neural networks, and applications, fifteen chapters by scholars and practitioners from around the world cover topics like: feature selection, cost-sensitive classification, heuristic search-based stacking, search engine design, Bayesian learning, the role of sampling, the gamma test, the use of neural networks for small data sets, and cluster analysis. The techniques are applied to on-line shopping, medical data, credit card use, and archeological data. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Book Details

Published
November 30, 2001
Publisher
IGI Publishing
Pages
295
Format
Hardcover
ISBN
9781930708266

Similar books