Data Mining : Practical Machine Learning Tools and Techniques, Second Edition

Much anticipated second edition of the highly-acclaimed reference on data mining and machine learning.

Bibliographic Details
Main Author: Witten, Ian H. (Author)
Other Involved Persons: Frank, Eibe (Contributor)
Format: eBook
Language:English
Published: San Francisco : Elsevier Science & Technology 2005
Edition:2nd ed.
ISBN:9780080477022
008047702X
9780120884070
0120884070
Series:The Morgan Kaufmann Series in Data Management Systems Ser
Item Description:Description based on publisher supplied metadata and other sources
Physical Description:1 online resource (558 pages)
Subjects:
Other Editions:Show all 2 Editions
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520 |a Intro -- CONTENTS -- Foreword -- Preface -- PART I: MACHINE LEARNING TOOLS AND TECHNIQUES -- 1 What's it all about? -- 2 Input: Concepts, instances, and attributes -- 3 Output: Knowledge representation -- 4 Algorithms: The basic methods -- 5 Credibility: Evaluating what's been learned -- 6 Implementations: Real machine learning schemes -- 7 Transformations: Engineering the input and output -- 8 Moving on: Extensions and applications -- PART II: THE WEKA MACHINE LEARNING WORKBENCH -- 9 Introduction to Weka -- 10 The Explorer -- 11 The Knowledge Flow Interface -- 12 The Experimenter -- 13 The Command-Line Interface -- 14 Embedded machine learning -- 15 Writing New Learning Schemes -- References -- Index -- About the Authors. 
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