Machine Learning and Data Mining: Methods and Applications |
| Editor: Ryszad S. Michalski (George Mason Univ., Fairfax); Editor: Ivan Bratko (Univ. of Ljubljana, Slovenia); Editor: Miroslav Kubat (Univ. of South Western Louisiana, Lafayette ) |
| Being able to extract meaningful patterns and strategic knowledge from large stores of information held electronically is increasingly a challenge facing the business and science worlds. In response, methods are being developed for discovering patterns and general rules from the information in databases, data warehouses and document information systems. This book is the first major text dedicated to issues at the intersection of machine learning and data mining  two interrelated fields that provide the foundations for these methods. Written by a team of international experts Machine Learning and Data Mining presents an exciting contribution addressing the new challenge. It provides an introduction to basic methods and its coverage spans the analysis of numerical data, text, images and sound. Most impressively, the book describes applications across a wide spectrum of real world problems, in domains such as engineering, control, biology, medicine and music
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| Cloth Bound |
472 Pages, 7-1/2 x 9-1/4 in.
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Item #:
Price: |
0471971995
$125.00 |
John Wiley & Sons, Inc. | |
