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Empirical Approach to Machine Learning

Overview of attention for book
Empirical Approach to Machine Learning
Springer International Publishing

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction
  3. Altmetric Badge
    Chapter 2 Brief Introduction to Statistical Machine Learning
  4. Altmetric Badge
    Chapter 3 Brief Introduction to Computational Intelligence
  5. Altmetric Badge
    Chapter 4 Empirical Approach—Introduction
  6. Altmetric Badge
    Chapter 5 Empirical Fuzzy Sets and Systems
  7. Altmetric Badge
    Chapter 6 Anomaly Detection— Empirical Approach
  8. Altmetric Badge
    Chapter 7 Data Partitioning— Empirical Approach
  9. Altmetric Badge
    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
  12. Altmetric Badge
    Chapter 11 Applications of Autonomous Data Partitioning
  13. Altmetric Badge
    Chapter 12 Applications of Autonomous Learning Multi-model Systems
  14. Altmetric Badge
    Chapter 13 Applications of Deep Rule-Based Classifiers
  15. Altmetric Badge
    Chapter 14 Applications of Semi-supervised Deep Rule-Based Classifiers
  16. Altmetric Badge
    Chapter 15 Epilogue
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Title
Empirical Approach to Machine Learning
Published by
Springer International Publishing, December 2018
DOI 10.1007/978-3-030-02384-3
ISBNs
978-3-03-002383-6, 978-3-03-002384-3
Authors

Angelov, Plamen P., Gu, Xiaowei

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