Lecture Notes in Artificial Intelligence

Machine Learning and Data Mining in Pattern Recognition

4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005, Proceedings

Editors: Perner, Petra, Imiya, Atsushi (Eds.)

Buy this book

eBook $139.00
price for USA (gross)
  • ISBN 978-3-540-31891-0
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $179.00
price for USA
  • ISBN 978-3-540-26923-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

We met again in front of the statue of Gottfried Wilhelm von Leibniz in the city of Leipzig. Leibniz, a famous son of Leipzig, planned automatic logical inference using symbolic computation, aimed to collate all human knowledge. Today, artificial intelligence deals with large amounts of data and knowledge and finds new information using machine learning and data mining. Machine learning and data mining are irreplaceable subjects and tools for the theory of pattern recognition and in applications of pattern recognition such as bioinformatics and data retrieval. This was the fourth edition of MLDM in Pattern Recognition which is the main event of Technical Committee 17 of the International Association for Pattern Recognition; it started out as a workshop and continued as a conference in 2003. Today, there are many international meetings which are titled “machine learning” and “data mining”, whose topics are text mining, knowledge discovery, and applications. This meeting from the first focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the viewpoints of machine learning and data mining. Though it was a challenging program in the late 1990s, the idea has inspired new starting points in pattern recognition and effects in other areas such as cognitive computer vision.

Table of contents (68 chapters)

  • On ECOC as Binary Ensemble Classifiers

    Ko, J. (et al.)

    Pages 1-10

  • Incremental Classification Rules Based on Association Rules Using Formal Concept Analysis

    Gupta, Anamika (et al.)

    Pages 11-20

  • Parameter Inference of Cost-Sensitive Boosting Algorithms

    Sun, Yanmin (et al.)

    Pages 21-30

  • Finite Mixture Models with Negative Components

    Zhang, Baibo (et al.)

    Pages 31-41

  • MML-Based Approach for Finite Dirichlet Mixture Estimation and Selection

    Bouguila, Nizar (et al.)

    Pages 42-51

Buy this book

eBook $139.00
price for USA (gross)
  • ISBN 978-3-540-31891-0
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $179.00
price for USA
  • ISBN 978-3-540-26923-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Machine Learning and Data Mining in Pattern Recognition
Book Subtitle
4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005, Proceedings
Editors
  • Petra Perner
  • Atsushi Imiya
Series Title
Lecture Notes in Artificial Intelligence
Series Volume
3587
Copyright
2005
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-540-31891-0
DOI
10.1007/b138149
Softcover ISBN
978-3-540-26923-6
Edition Number
1
Number of Pages
XVIII, 698
Topics