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PART I: Introduction to Data Mining Ch 1 What's It All About? Ch 2 Input: Concepts, Instances, Attributes Ch 3 Output: Knowledge Representation Ch 4 Algorithms: The Basic Methods Ch 5 Credibility: Evaluating What's Been Learned PART II: Advanced Data Mining
Ch 6 Implementations: Real Machine Learning Schemes Ch 7 Data Transformation Ch 8 Ensemble Learning Ch 9 Moving On: Applications and Beyond PART III: The Weka Data MiningWorkbench Ch 10 Introduction to Weka Ch 11 The Explorer Ch 12 The Knowledge Flow Interface Ch 13 The Experimenter Ch 14 The Command-Line Interface Ch 15 Embedded Machine Learning Ch 16 Writing New Learning Schemes Ch 17 Tutorial Exercises for the Weka Explorer
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Add Data Mining: Practical Machine Learning Tools and Techniques, Data Mining: Practical Machine Learning Tools and Techniques 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 hi, Data Mining: Practical Machine Learning Tools and Techniques to the inventory that you are selling on WonderClubX
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Add Data Mining: Practical Machine Learning Tools and Techniques, Data Mining: Practical Machine Learning Tools and Techniques 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 hi, Data Mining: Practical Machine Learning Tools and Techniques to your collection on WonderClub |