- 374 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
New Advances in Machine Learning
About this book
The purpose of this book is to provide an up-to-date and systematical introduction to the principles and algorithms of machine learning. The definition of learning is broad enough to include most tasks that we commonly call "learning" tasks, as we use the word in daily life. It is also broad enough to encompass computers that improve from experience in quite straightforward ways. The book will be of interest to industrial engineers and scientists as well as academics who wish to pursue machine learning. The book is intended for both graduate and postgraduate students in fields such as computer science, cybernetics, system sciences, engineering, statistics, and social sciences, and as a reference for software professionals and practitioners. The wide scope of the book provides a good introduction to many approaches of machine learning, and it is also the source of useful bibliographical information.
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access New Advances in Machine Learning by Yagang Zhang in PDF and/or ePUB format, as well as other popular books in Computer Science & Programming Games. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- New Advances in Machine Learning
- Contents
- Preface
- 1. Introduction to Machine Learning
- 2. Machine Learning Overview
- 3. Types of Machine Learning Algorithms
- 4. Methods for Pattern Classification
- 5. Classification of support vector machine and regression algorithm
- 6. Classifiers Association for High Dimensional Problem: Application to Pedestrian Recognition
- 7. From Feature Space to Primal Space:KPCA and Its Mixture Model
- 8. Machine Learning for Multi-stage Selection of Numerical Methods*
- 9. Hierarchical Reinforcement Learning Using a Modular Fuzzy Model for Multi-Agent Problem
- 10. Random Forest-LNS Architecture and Vision
- 11. An Intelligent System for Container Image Recognition using ART2-based Self-Organizing Supervised Learning Algorithm
- 12. Data mining with skewed data
- 13. Scaling up instance selection algorithms by dividing-and-conquering
- 14. Ant Colony Optimization
- 15. Mahalanobis Support Vector Machines Made Fast and Robust
- 16. On-line learning of fuzzy rule emulated networks for a class of unknown nonlinear discrete-time controllers with estimated linearization
- 17. Knowledge Structures for Visualising Advanced Research and Trends
- 18. Dynamic Visual Motion Estimation
- 19. Concept Mining and Inner Relationship Discovery from Text
- 20. Cognitive Learning for Sentence Understanding
- 21. A Hebbian Learning Approach
- 22. A Novel Credit Assignment to a Rule with Probabilistic State Transition