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Predictor models in software engineering (PROMISE)
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Source International Conference on Software Engineering archive
Proceedings of the 27th international conference on Software engineering table of contents
St. Louis, MO, USA
WORKSHOP SESSION: Worhshops table of contents
Pages: 692 - 692  
Year of Publication: 2005
ISBN:1-59593-963-2
Authors
Jelber Sayyad Shirabad  University of Ottawa, Canada
Tim Menzies  Portland State University
Sponsors
ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
Bibliometrics
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DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1062455.1062617
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ABSTRACT

No abstract available


INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.6 Learning
          Subjects: Concept learning

Additional Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.8 Metrics
          Subjects: Performance measures

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.6 Learning
          Subjects: Induction


General Terms:
Algorithms, Experimentation, Measurement, Performance


Keywords:
data mining, empirical studies, machine learning, predictive software models, software engineering

Collaborative Colleagues:
Jelber Sayyad Shirabad: colleagues
Tim Menzies: colleagues

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