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Empirical Approach to Machine Learning

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Cover of 'Empirical Approach to Machine Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Brief Introduction to Statistical Machine Learning
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    Chapter 3 Brief Introduction to Computational Intelligence
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    Chapter 4 Empirical Approach—Introduction
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    Chapter 5 Empirical Fuzzy Sets and Systems
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    Chapter 6 Anomaly Detection— Empirical Approach
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    Chapter 7 Data Partitioning— Empirical Approach
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    Chapter 8 Autonomous Learning Multi-model Systems
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    Chapter 9 Transparent Deep Rule-Based Classifiers
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    Chapter 10 Applications of Autonomous Anomaly Detection
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    Chapter 11 Applications of Autonomous Data Partitioning
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    Chapter 12 Applications of Autonomous Learning Multi-model Systems
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    Chapter 13 Applications of Deep Rule-Based Classifiers
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    Chapter 14 Applications of Semi-supervised Deep Rule-Based Classifiers
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    Chapter 15 Epilogue
Attention for Chapter 2: Brief Introduction to Statistical Machine Learning
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