Gives a solid basis for conducting performance evaluations of learning algorithms in practical settings with an emphasis on classification algorithms.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Nathalie Japkowicz is Professor of Computer Science at American University. She is a former assistant professor at Dalhousie University and lecturer at Ohio State University. Japkowicz co-organized numerous workshops on classifier evaluation and the class imbalance problem at AAAI and ICML. She has published many articles in peer-reviewed journals and conference proceedings.
Inhaltsangabe
1. Introduction 2. Machine learning and statistics overview 3. Performance measures I 4. Performance measures II 5. Error estimation 6. Statistical significance testing 7. Data sets and experimental framework 8. Recent developments 9. Conclusion Appendix A: statistical tables Appendix B: additional information on the data Appendix C: two case studies.
1. Introduction 2. Machine learning and statistics overview 3. Performance measures I 4. Performance measures II 5. Error estimation 6. Statistical significance testing 7. Data sets and experimental framework 8. Recent developments 9. Conclusion Appendix A: statistical tables Appendix B: additional information on the data Appendix C: two case studies.
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