Data Mining: Practical Machine Learning Tools and Techniques (The Morgan Kaufmann Series in Data Management Systems)
Author: Ian H. Witten – Eibe Frank – Mark A. Hall
ISBN-10 书号: 0123748569
ISBN-13 书号: 9780123748560
Edition 版本: 3
Release Finelybook 出版日期: 2011-01-20
pages 页数: 664

$69.95


Book Description to Finelybook sorting

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition 版本, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.
Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research.
The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise.

Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects
Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks―in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization


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Data Mining Practical Machine Learning Tools and Techniques, 3rd Edition
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