Data Mining: Practical Machine Learning Tools and Techniques, 2nd Edition

Book Description

, Second Edition, describes data mining techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references.

The highlights of this new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive ; comprehensive information on neural networks; a new section on Bayesian networks; and much more.

This text is designed for information practitioners, programmers, consultants, developers, information managers, specification writers as well as professors and students of graduate-level data mining and machine learning courses.

  • methods at the heart of successful data mining―including tried and true techniques as well as leading edge methods
  • Performance improvement techniques that work by transforming the input or output

Table of Contents

Part I Machine learning tools and techniques
Chapter 1 What’S It All About?
Chapter 2 Input: Concepts, Instances, And Attributes
Chapter 3 Output: Knowledge Representation
Chapter 4 Algorithms: The Basic Methods
Chapter 5 Credibility: Evaluating What’S Been Learned
Chapter 6 Implementations: Real Machine Learning Schemes
Chapter 7 Transformations: The Input And Output
Chapter 8 Moving On: Extensions And Applications

Part II The Weka machine learning workbench
Chapter 9 Introduction To Weka
Chapter 10 The Explorer
Chapter 11 The Knowledge Flow Interface
Chapter 12 The Experimenter
Chapter 13 The Command-Line Interface
Chapter 14 Embedded Machine Learning
Chapter 15 Writing New Learning Schemes

Book Details

  • Title: Data Mining: Practical Machine Learning Tools and Techniques, 2nd Edition
  • Author: ,
  • Length: 560 pages
  • Edition: 2
  • Language: English
  • Publisher:
  • Publication Date: 2005-06-22
  • ISBN-10: 0120884070
  • ISBN-13: 9780120884070
Download LinkFormatSize (MB)Upload Date
Download from UsersCloudTrue PDF5.209/19/2018
How to Download? Report Dead Links & Get a Copy