Open access peer-reviewed Edited Volume

New Advances in Machine Learning

Book metrics overview

67,256 Chapter Downloads

View Full Metrics

Academic Editor

Yagang Zhang
Yagang Zhang

North China Electric Power University,
China

Published01 February 2010

Doi10.5772/225

ISBN978-953-307-034-6

eBook (PDF) ISBN978-953-51-5906-3

Copyright year2010

Number of pages374

Read more
Order Print Copy

Edited Volume and chapters are indexed in

  • Google Scholar
  • DOAB
  • Crossref
  • Dimension
  • OpenAIRE
  • AZ ebsco
  • Worldcat
Show more

Table of Contents

Open access  chapters

1. Introduction to Machine Learning

By Taiwo Oladipupo Ayodele

4,107
4
2. Machine Learning Overview

By Taiwo Oladipupo Ayodele

4,384
8
3. Types of Machine Learning Algorithms

By Taiwo Oladipupo Ayodele

11,233
70
2,231
6. Classifiers Association for High Dimensional Problem: Application to Pedestrian Recognition

By Laetitia Leyrit, Thierry Chateau and Jean-Thierry Lapreste

2,187
2,266
2,447
12. Data Mining with Skewed Data

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

4,715
13. Scaling up Instance Selection Algorithms by Dividing-and-Conquering

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

2,163
14. Ant Colony Optimization

By Benlian Xu, Jihong Zhu and Qinlan Chen

2,638
3
15. Mahalanobis Support Vector Machines Made Fast and Robust

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

2,993
1
18. Dynamic Visual Motion Estimation

By Volker Willert and Julian Eggert

2,143
2,290

IMPACT OF THIS BOOK AND ITS CHAPTERS

67,256 Total Chapter Downloads

5,342 Total Chapter Views

110 Crossref Citations

132 Web of Science Citations

395 Dimensions Citations

21 Altmetric Score

Order a print copy of this book

£139 (ex. VAT)*

Hardcover | Printed Full Colour

IntechOpen Contributor? Get your Discount

FREE SHIPPING WORLDWIDE

Order & Delivery info

* Residents of European Union countries need to add a Book Value-Added Tax Rate based on their country of residence. Institutions and companies, registered as VAT taxable entities in their own EU member state, will not pay VAT by providing IntechOpen with their VAT registration number. This is made possible by the EU reverse charge method.

Instructor? Request an Exam Copy