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Home / Proceedings / AAAI Workshop Papers 2006 /

Evaluation Methods for Machine Learning

Contents

  • Contents
    PDF
  • Preface

    Chris Drummond, William Elazmeh, Nathalie Japkowicz

    PDF
  • Machine Learning as an Experimental Science (Revisited)

    Chris Drummond

    PDF
  • Why Question Machine Learning Evaluation Methods (An Illustrative Review of the Shortcomings of Current Methods)

    Nathalie Japkowicz

    PDF
  • Evaluating Model Selection Abilities of Performance Measures

    Jin Huang

    PDF
  • Evaluating Probability Estimates from Decision Trees

    Nitesh Chawla, David Cieslak

    PDF
  • Beyond Accuracy, F-score and ROC: A Family of Discriminant Measures for Performance Evaluation

    Marina Sokolova, Nathalie Japkowicz, Stan Szpakowicz

    PDF
  • Evaluation of Classifiers: Practical Considerations for Security Applications

    Alvaro A. Cardenas, John S. Baras

    PDF
  • Confidence Interval for the Difference in Classification Error

    William Elazmeh, Nathalie Japkowicz, Stan Matwin

    PDF
  • Evaluating the Explanatory Value of Bayesian Network Structure Learning Algorithms

    Patrick Shaughnessy, Gary Livingston

    PDF
  • Organizing Committee

    Chris Drummond, William Elazmeh, and Nathalie Japkowicz

    PDF

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