Fuzzy Modeling And Genetic Algorithms For Data Mining And Exploration (Record no. 18368)
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| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
|---|---|
| ISBN | 9788131200926 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.312 |
| Author Mark | COX |
| 100 ## - MAIN ENTRY--AUTHOR | |
| Author Name | Cox, Earl |
| 245 ## - TITLE STATEMENT | |
| Title | Fuzzy Modeling And Genetic Algorithms For Data Mining And Exploration |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of Publication | New Delhi |
| Name of publisher, distributor, etc. | Morgann Kaufmann, |
| Date of publication, distribution, etc. | 2005 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pages | xxi, 530 p. |
| Dimensions | 18x24 cm |
| 500 ## - GENERAL NOTE | |
| General note | Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As you’ll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems. You don’t need a background in fuzzy modeling or genetic algorithms to benefit, for this book provides it, along with detailed instruction in methods that you can immediately put to work in your own projects. The author provides many diverse examples and also an extended example in which evolutionary strategies are used to create a complex scheduling system.<br/>Written to provide analysts, engineers, and managers with the background and specific instruction needed to develop and implement more effective data mining systems<br/>Helps you to understand the trade-offs implicit in various models and model architectures<br/>Provides extensive coverage of fuzzy SQL querying, fuzzy clustering, and fuzzy rule induction<br/>Lays out a roadmap for exploring data, selecting model system measures, organizing adaptive feedback loops, selecting a model configuration, implementing a working model, and validating the final model<br/>In an extended example, applies evolutionary programming techniques to solve a complicated scheduling problem<br/>Presents examples in C, C++, Java, and easy-to-understand pseudo-code<br/>Extensive online component, including sample code and a complete data mining workbench<br/>"synopsis" may belong to another edition of this title |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Including with reference and index |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Subject / Department | Fuzzy Modeling, Genetic Algorithm, Distributed Knowledge, Data Mining, Fuzzy System for Business Process, Concept of Fuzzy Logic, Fuzzy SQL, Fuzzy Clustering, Genetic Tuning of Fuzzy Moodels |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Book |
| Withdrawn status | Not for loan | Collection code | Permanent Location | Current Location | Shelving Location | Date acquired | Source of acquisition | Price | Inventory number | Full Call Number | Accession No./Barcode | Date last seen | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Computer Science | Air University Multan Campus Library | Air University Central Library Islamabad | Computer Science | 04/11/2011 | Multiline Books | 971.00 | 01139 | 006.312 COX | P000116 | 08/28/2023 | Book |