• Skip to main content
  • Skip to primary sidebar
AAAI

AAAI

Association for the Advancement of Artificial Intelligence

    • AAAI

      AAAI

      Association for the Advancement of Artificial Intelligence

  • About AAAIAbout AAAI
    • News
    • Officers and Committees
    • Staff
    • Bylaws
    • Awards
      • Fellows Program
      • Classic Paper Award
      • Dissertation Award
      • Distinguished Service Award
      • Allen Newell Award
      • Outstanding Paper Award
      • AI for Humanity Award
      • Feigenbaum Prize
      • Patrick Henry Winston Outstanding Educator Award
      • Engelmore Award
      • AAAI ISEF Awards
      • Senior Member Status
      • Conference Awards
    • Partnerships
    • Resources
    • Mailing Lists
    • Past Presidential Addresses
    • AAAI 2025 Presidential Panel on the Future of AI Research
    • Presidential Panel on Long-Term AI Futures
    • Past Policy Reports
      • The Role of Intelligent Systems in the National Information Infrastructure (1995)
      • A Report to ARPA on Twenty-First Century Intelligent Systems (1994)
    • Logos
  • aaai-icon_ethics-diversity-line-yellowEthics & Diversity
  • Conference talk bubbleConferences & Symposia
    • AAAI Conference
    • AIES AAAI/ACM
    • AIIDE
    • EAAI
    • HCOMP
    • IAAI
    • ICWSM
    • Spring Symposia
    • Summer Symposia
    • Fall Symposia
    • Code of Conduct for Conferences and Events
  • PublicationsPublications
    • AI Magazine
    • Conference Proceedings
    • AAAI Publication Policies & Guidelines
    • Request to Reproduce Copyrighted Materials
    • Contribute
    • Order Proceedings
  • aaai-icon_ai-magazine-line-yellowAI Magazine
  • MembershipMembership
    • Member Login
    • Chapters

  • Career CenterAI Jobs
  • aaai-icon_ai-topics-line-yellowAITopics
  • aaai-icon_contact-line-yellowContact

  • Twitter
  • Facebook
  • LinkedIn
Home / Proceedings / AAAI Workshop Papers 2007 /

Evaluation Methods for Machine Learning II

Contents

  • A Review of Performance Evaluation Measures for Hierarchical Classifiers

    Eduardo P. Costa, Ana C. Lorena, Andre C. P. L. F. Carvalho, Alex A. Freitas

    PDF
  • Making Evaluation Robust but Robust to What?

    Chris Drummond

    PDF
  • Insights from Predicting Pediatric Asthma Exacerbations from Retrospective Clinical Data

    William Elazmeh, Dympna O'Sullivan, Stan Matwin, Wojtek Michalowski, Ken farion

    PDF
  • Classifier Utility Visualization by Distance-Preserving Projection of High Dimensional Performance Data

    Nathalie Japkowicz, Pritika Sanghi, Peter Tischer

    PDF
  • A Framework for Analyzing Skew in Evaluation Metrics

    Alexander Liu, Joydeep Ghosh, Cheryl Martin

    PDF
  • Obtaining Calibrated Probabilities from Boosting

    Alexandru Niculescu-Mizil, Rich Caruana

    PDF
  • On Comparison of Feature Selection Algorithms

    Payam Refaeilzadeh, Lei Tang, Huan Liu

    PDF
  • Scoring Hypotheses from Threat Detection Technologies: Analogies to Machine Learning Evaluation

    Robert C. Schrag, Masami Takikawa

    PDF
  • Classifier Loss under Metric Uncertainty

    David B. Skalak, Alexandru Niculescu-Mizil, Rich Caruana

    PDF
  • Organizing Committee

    Chris Drummond, William Elazmeh, Nathalie Japkowicz, and Sofus A. Macskassy

    PDF
  • Preface

    Chris Drummond, William Elazmeh, Nathalie Japkowicz, and Sofus A. Macskassy

    PDF

Primary Sidebar