Synopsis
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.
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Heuristic and Optimization for Knowledge Discovery
Seller: WeBuyBooks, Rossendale, LANCS, United Kingdom
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Condition: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind. Seller Inventory # wbs7538220821
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Heuristic and Optimization for Knowledge Discovery
Seller: killarneybooks, Inagh, CLARE, Ireland
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Hardcover. Condition: Good. Hardcover, [x] + 290 pages, NOT ex-library. Front blank endpaper is creased and stuck to the front board. Book is clean and bright with unmarked text, free of inscriptions and stamps. Boards show gentle handling wear. Published without a dust jacket. -- 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. -- Contents: Section One: Introduction: - 1 Introducing Data Mining and Knowledge Discovery; Section Two: Search and Optimization: - 2 A Heuristic Algorithm for Feature Selection Based on Optimization Techniques; 3 Cost-Sensitive Classification Using Decision Trees, Boosting and MetaCost; 4 Heuristic Search-Based Stacking of Classifiers; 5 Designing Component-Based Heuristic Search Engines for Knowledge Discovery; 6 Clustering Mixed Incomplete Data; Section Three: Statistics and Data Mining: - 7 Bayesian Learning; 8 How Size Matters: The Role of Sampling in Data Mining; 9 The Gamma Test; Section Four: Neural Networks and Data Mining: - 10 Neural Networks: Their Use and Abuse for Small Data Sets; 11 How to Train Multilayer Perceptrons Efficiently with Large Data Sets; Section Five: Applications: - 12 Cluster Analysis of Marketing Data Examining On-line Shopping Orientation: A Comparison of K-means and Rough Clustering Approaches; 13 Heuristics in Medical Data Mining; 14 Understanding Credit Card User's Behaviour: A Data Mining Approach; 15 Heuristic Knowledge Discovery for Archaeological Data Using Genetic Algorithms and Rough Sets; Index. Seller Inventory # 005424