Open access peer-reviewed Edited Volume

New Advances in Machine Learning

Edited by Yagang Zhang

University of Pristina, Kosovo

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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New Advances in Machine LearningEdited by Yagang Zhang

Published: February 1st 2010

DOI: 10.5772/225

ISBN: 978-953-307-034-6

Copyright year: 2010

Books open for chapter submissions

45199 Total Chapter Downloads

12 Crossref Citations

13 Web of Science Citations

38 Dimensions Citations

chaptersDownloads

Open access peer-reviewed

1. Introduction to Machine Learning

By Taiwo Oladipupo Ayodele

2368

Open access peer-reviewed

2. Machine Learning Overview

By Taiwo Oladipupo Ayodele

2722

Open access peer-reviewed

3. Types of Machine Learning Algorithms

By Taiwo Oladipupo Ayodele

8867

Open access peer-reviewed

4. Methods for Pattern Classification

By Yizhang Guan

1363

Open access peer-reviewed

5. Classification of Support Vector Machine and Regression Algorithm

By Cai-Xia Deng, Li-Xiang Xu and Shuai Li

1396

Open access peer-reviewed

6. Classifiers Association for High Dimensional Problem: Application to Pedestrian Recognition

By Laetitia Leyrit, Thierry Chateau and Jean-Thierry Lapreste

1412

Open access peer-reviewed

7. From Feature Space to Primal Space: KPCA and Its Mixture Model

By Haixian Wang

1811

Open access peer-reviewed

8. Machine Learning for Multi-stage Selection of Numerical Methods

By Victor Eijkhout and Erika Fuentes

1468

Open access peer-reviewed

9. Hierarchical Reinforcement Learning Using a Modular Fuzzy Model for Multi-Agent Problem

By Toshihiko Watanabe

1250

Open access peer-reviewed

10. Random Forest-LNS Architecture and Vision

By Hassab Elgawi Osman

1513

Open access peer-reviewed

11. An Intelligent System for Container Image Recognition using ART2-based Self-Organizing Supervised Learning Algorithm

By Kwang-Baek Kim, Sungshin Kim and Young Woon Woo

1647

Open access peer-reviewed

12. Data Mining with Skewed Data

By Manoel Fernando Alonso Gadi, Alair Pereira do Lago and Jorn Mehnen

4021

Open access peer-reviewed

13. Scaling up Instance Selection Algorithms by Dividing-and-Conquering

By Aida de Haro-Garcia, Juan Antonio Romero del Castillo and Nicolas Garcia-Pedrajas

1295

Open access peer-reviewed

14. Ant Colony Optimization

By Benlian Xu, Jihong Zhu and Qinlan Chen

1961

Open access peer-reviewed

15. Mahalanobis Support Vector Machines Made Fast and Robust

By Xunkai Wei, Yinghong Li, Dong Liu and Liguang Zhan

2207

Open access peer-reviewed

16. On-line Learning of Fuzzy Rule Emulated Networks for a Class of Unknown Nonlinear Discrete-Time Controllers with Estimated Linearization

By Chidentree Treesatayapun

1376

Open access peer-reviewed

17. Knowledge Structures for Visualising Advanced Research and Trends

By Maria R. Lee and Tsung Teng Chen

1279

Open access peer-reviewed

18. Dynamic Visual Motion Estimation

By Volker Willert and Julian Eggert

1412

Open access peer-reviewed

19. Concept Mining and Inner Relationship Discovery from Text

By Jiayu Zhou and Shi Wang

1783

Open access peer-reviewed

20. Cognitive Learning for Sentence Understanding

By Yi Guo and Zhiqing Shao

1496

Open access peer-reviewed

21. A Hebbian Learning Approach for Diffusion Tensor Analysis and Tractography

By Dilek Goksel Duru

1465

Open access peer-reviewed

22. A Novel Credit Assignment to a Rule with Probabilistic State Transition

By Wataru Uemura

1087

Edited Volume and chapters are indexed in

  • Worldcat
  • OpenAIRE
  • Google Scholar
  • AZ ebsco
  • Base
  • CNKI
  • IET Inspec

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