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Lazy Learning

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Cover of 'Lazy Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Editorial
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    Chapter 2 Locally Weighted Learning
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    Chapter 3 Locally Weighted Learning for Control
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    Chapter 4 Voting over Multiple Condensed Nearest Neighbors
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    Chapter 5 Tolerating Concept and Sampling Shift in Lazy Learning Using Prediction Error Context Switching
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    Chapter 6 Discretisation in Lazy Learning Algorithms
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    Chapter 7 Intelligent Selection of Instances for Prediction Functions in Lazy Learning Algorithms
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    Chapter 8 The Racing Algorithm: Model Selection for Lazy Learners
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    Chapter 9 Context-Sensitive Feature Selection for Lazy Learners
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    Chapter 10 Computing Optimal Attribute Weight Settings for Nearest Neighbor Algorithms
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    Chapter 11 A Review and Empirical Evaluation of Feature Weighting Methods for a Class of Lazy Learning Algorithms
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    Chapter 12 Lazy Acquisition of Place Knowledge
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    Chapter 13 A Teaching Strategy for Memory-Based Control
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    Chapter 14 Lazy Incremental Learning of Control Knowledge for Efficiently Obtaining Quality Plans
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    Chapter 15 IGTree: Using Trees for Compression and Classification in Lazy Learning Algorithms
Attention for Chapter 15: IGTree: Using Trees for Compression and Classification in Lazy Learning Algorithms
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