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Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods

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Cover of 'Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Classification
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    Chapter 3 Understanding OWA Based Fuzzy Rough Sets
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    Chapter 4 Learning from Imbalanced Data
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    Chapter 5 Fuzzy Rough Set Based Classification of Semi-supervised Data
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    Chapter 6 Multi-instance Learning
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    Chapter 7 Multi-label Learning
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    Chapter 8 Conclusions and Future Work
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