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Learning to Classify Text Using Support Vector Machines
96,29 €*
ISBN-13:
9781461509073
Veröffentl:
2012
Seiten:
205
Autor:
Thorsten Joachims
Serie:
668, The Springer International Series in Engineering and Computer Science
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:
1. Introduction.- 1 Challenges.- 2 Goals.- 3 Overview and Structure of the Argument.- 4 Summary.- 2. Text Classification.- 1 Learning Task.- 2 Representing Text.- 3 Feature Selection.- 4 Term Weighting.- 5 Conventional Learning Methods.- 6 Performance Measures.- 7 Experimental Setup.- 3. Support Vector Machines.- 1 Linear Hard-Margin SVMs.- 2 Soft-Margin SVMs.- 3 Non-Linear SVMs.- 4 Asymmetric Misclassification Cost.- 5 Other Maximum-Margin Methods.- 6 Further Work and Further Information.- Theory.- 4. A Statistical Learning Model of text Classification for SVMs.- 5. Efficient Performance Estimators for SVMs.- Methods.- 6. Inductive Text Classification.- 7. Transductive Text Classification.- Algorithms.- 8. Training Inductive Support Vector Machines.- 9. Training Transductive Support Vector Machines.- 10. Conclusions.- Appendices.- SVM-Light Commands and Options.