Book Volume 6871 2011

Machine Learning and Data Mining in Pattern Recognition

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


ISBN: 978-3-642-23198-8 (Print) 978-3-642-23199-5 (Online)

Table of contents (44 chapters)

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  1. Front Matter

    Pages -

  2. Classification and Decision Theory

    1. Chapter

      Pages 1-15

      Quadratically Constrained Maximum a Posteriori Estimation for Binary Classifier

    2. Chapter

      Pages 16-30

      Hubness-Based Fuzzy Measures for High-Dimensional k-Nearest Neighbor Classification

    3. Chapter

      Pages 31-45

      Decisions: Algebra and Implementation

    4. Chapter

      Pages 46-59

      Smoothing Multinomial Naïve Bayes in the Presence of Imbalance

    5. Chapter

      Pages 60-74

      ACE-Cost: Acquisition Cost Efficient Classifier by Hybrid Decision Tree with Local SVM Leaves

    6. Chapter

      Pages 75-87

      Informative Variables Selection for Multi-relational Supervised Learning

    7. Chapter

      Pages 88-98

      Separability of Split Value Criterion with Weighted Separation Gains

    8. Chapter

      Pages 99-111

      Granular Instances Selection for Fuzzy Modeling

    9. Chapter

      Pages 112-126

      Parameter-Free Anomaly Detection for Categorical Data

    10. Chapter

      Pages 127-139

      Fuzzy Semi-supervised Support Vector Machines

    11. Chapter

      Pages 140-154

      GENCCS: A Correlated Group Difference Approach to Contrast Set Mining

    12. Chapter

      Pages 155-169

      Collective Classification Using Heterogeneous Classifiers

    13. Chapter

      Pages 170-184

      Spherical Nearest Neighbor Classification: Application to Hyperspectral Data

    14. Chapter

      Pages 185-198

      Adaptive Kernel Diverse Density Estimate for Multiple Instance Learning

    15. Chapter

      Pages 199-209

      Boosting Inspired Process for Improving AUC

  3. Theory of Learning

    1. Chapter

      Pages 210-223

      Investigation in Transfer Learning: Better Way to Apply Transfer Learning between Agents

    2. Chapter

      Pages 224-238

      Exploration Strategies for Learned Probabilities in Smart Terrain

    3. Chapter

      Pages 239-252

      Sensitivity Analysis for Weak Constraint Generation

    4. Chapter

      Pages 253-264

      Dictionary Learning Based on Laplacian Score in Sparse Coding

  4. Clustering

    1. Chapter

      Pages 265-279

      A Practical Approach for Clustering Transaction Data

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