Data Mining and Knowledge Discovery with Evolutionary Algorithms (Natural Computing Series) - Image 1

Price loading...

Springer Data Mining and Knowledge Discovery with Evolutionary Algorithms (Natural Computing Series)

Name: Data Mining and Knowledge Discovery with Evolutionary Algorithms (Natural Computing Series)
Brand: Springer

74 black & white illustrations, 10 black

AI & Machine Learning

Price History & Forecast

No Price Data Available

Price history will appear here once data is collected from Amazon.

Price Distribution

No price data available for histogram

Description

This book addresses the integration of two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increas ingly popular in the last few years, and their integration is currently an area of active research. In essence, data mining consists of extracting valid, comprehensible, and in teresting knowledge from data. Data mining is actually an interdisciplinary field, since there are many kinds of methods that can be used to extract knowledge from data. Arguably, data mining mainly uses methods from machine learning (a branch of artificial intelligence) and statistics (including statistical pattern recog nition). Our discussion of data mining and evolutionary algorithms is primarily based on machine learning concepts and principles. In particular, in this book we emphasize the importance of discovering comprehensible, interesting knowledge, which the user can potentially use to make intelligent decisions. In a nutshell, the motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions (rules or another form of knowl edge representation). In contrast, most rule induction methods perform a local, greedy search in the space of candidate rules. Intuitively, the global search of evolutionary algorithms can discover interesting rules and patterns that would be missed by the greedy search.

Product Specifications

Brand: Springer
Model: 74 black & white illustrations, 10 black
Format: hardcover
ASIN: 3540433317
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 21 August 2002
Listed Since: 22 January 2007

Barcode

No barcode data available

Springer Data Mining and Knowledge Discovery with Evolutionary Algorithms (Natural Computing Series)

Price History & Forecast

No Price Data Available

Price Distribution

Description

Product Specifications

Barcode

Similar Products You Might Like

Automating the Design of Data Mining Algorithms: An Evolutionary Computation Approach (Natural Computing Series)

Advanced Methods for Knowledge Discovery from Complex Data (Advanced Information and Knowledge Processing)

Springer Deep Neural Evolution - Deep Learning and EC Book

Data Mining: Concepts, Models and Techniques: 12 (Intelligent Systems Reference Library, 12)

Evolutionary Decision Trees in Large-Scale Data Mining: 59 (Studies in Big Data, 59)

Handbook of Evolutionary Machine Learning (Genetic and Evolutionary Computation)

Data-Driven Evolutionary Optimization: Integrating Evolutionary Computation, Machine Learning and Data Science: 975 (Studies in Computational Intelligence, 975)

Data-Driven Evolutionary Optimization: Integrating Evolutionary Computation, Machine Learning and Data Science: 975 (Studies in Computational Intelligence, 975)

Data Mining using Neural Networks: The Art and Science of Rule Discovery for Data Mining

Advanced Techniques in Knowledge Discovery and Data Mining (Advanced Information and Knowledge Processing)

Multimodal Optimization by Means of Evolutionary Algorithms (Natural Computing Series)

Springer Introduction to Evolutionary Algorithms Book

Introduction to Evolutionary Algorithms (Decision Engineering)

Knowledge Incorporation in Evolutionary Computation: 167 (Studies in Fuzziness and Soft Computing, 167)

Innovations in Big Data Mining and Embedded Knowledge: 159 (Intelligent Systems Reference Library, 159)

Knowledge Incorporation in Evolutionary Computation: 167 (Studies in Fuzziness and Soft Computing, 167)

Knowledge Discovery in Multiple Databases (Advanced Information and Knowledge Processing)

Evolutionary Data Clustering: Algorithms and Applications (Algorithms for Intelligent Systems)

Evolutionary Computation: Theory and Applications

Evolutionary Learning: Advances in Theories and Algorithms

Evolutionary Algorithms: The Role of Mutation and Recombination (Natural Computing Series)

Advanced Data Mining Techniques

Machine Learning and Data Mining

Lee Men's Luke Slim Fit Tapered Leg Jeans, Declaration, 29 W/30 L