Machine Learning and Data Mining in Pattern Recognition

7th International Conference, MLDM 2011, New York, NY, USA, August 30 – September 3, 2011. Proceedings

  • Petra Perner
Conference proceedings MLDM 2011

DOI: 10.1007/978-3-642-23199-5

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6871)

Table of contents (44 papers)

  1. Front Matter
  2. Classification and Decision Theory

    1. Hubness-Based Fuzzy Measures for High-Dimensional k-Nearest Neighbor Classification
      Nenad Tomašev, Miloš Radovanović, Dunja Mladenić, Mirjana Ivanović
      Pages 16-30
    2. Decisions: Algebra and Implementation
      Antonina Danylenko, Jonas Lundberg, Welf Löwe
      Pages 31-45
    3. Smoothing Multinomial Naïve Bayes in the Presence of Imbalance
      Alexander Y. Liu, Cheryl E. Martin
      Pages 46-59
    4. Informative Variables Selection for Multi-relational Supervised Learning
      Dhafer Lahbib, Marc Boullé, Dominique Laurent
      Pages 75-87
    5. Granular Instances Selection for Fuzzy Modeling
      S. Sakinah S. Ahmad, Witold Pedrycz
      Pages 99-111
    6. Parameter-Free Anomaly Detection for Categorical Data
      Shu Wu, Shengrui Wang
      Pages 112-126
    7. Fuzzy Semi-supervised Support Vector Machines
      Houda Benbrahim
      Pages 127-139
    8. GENCCS: A Correlated Group Difference Approach to Contrast Set Mining
      Mondelle Simeon, Robert Hilderman
      Pages 140-154
    9. Collective Classification Using Heterogeneous Classifiers
      Zehra Cataltepe, Abdullah Sonmez, Kadriye Baglioglu, Ayse Erzan
      Pages 155-169
    10. Adaptive Kernel Diverse Density Estimate for Multiple Instance Learning
      Tao Xu, Iker Gondra, David Chiu
      Pages 185-198
    11. Boosting Inspired Process for Improving AUC
      Victor S. Sheng, Rahul Tada
      Pages 199-209
  3. Theory of Learning

    1. Investigation in Transfer Learning: Better Way to Apply Transfer Learning between Agents
      Luiz Antonio Celiberto Junior, Jackson P. Matsuura
      Pages 210-223
    2. Sensitivity Analysis for Weak Constraint Generation
      Jamshaid G. Mohebzada, Michael M. Richter, Guenther Ruhe
      Pages 239-252

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2011, held in New York, NY, USA.

The 44 revised full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized in topical sections on classification and decision theory, theory of learning, clustering, appilication in medicine, Webmining and information mining; and machine learning and image mining.

Keywords

algorithmic learning data analysis kernel methods suppor vector machine text analysis

Editors and affiliations

  • Petra Perner
    • 1
  1. 1.Intitute of Computer Vision and Applied Computer Sciences, IBaILeipzigGermany

Bibliographic information

  • Copyright Information Springer-Verlag GmbH Berlin Heidelberg 2011
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-23198-8
  • Online ISBN 978-3-642-23199-5
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349