We describe in detail an implementation, called BoosTexter, of the new boosting algorithms for text categorization tasks. We present results comparing the. BoosTexter is a general purpose machine-learning program based on boosting for building a BoosTexter: A boosting-based system for text categorization. BoosTexter: A Boosting-based Systemfor Text Categorization . In Advances in Neural Information Processing Systems 8 (pp. ). 8.
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Advances in Neural Information Processing Systems, Articles 1—20 Show more. An evaluation of statistical approaches to text categorization.
Nonlinear estimation and classification, Reducing multiclass to binary: Large margin classification using the perceptron algorithm Y Freund, RE Schapire Machine learning 37 3, Email address for updates.
The system can’t perform the operation now. The boosting approach to machine learning: Get my own profile Cited by View all All Since Citations h-index 75 54 iindex McCarthyDanielle S.
A decision-theoretic generalization of on-line learning and an application to boosting Y Freund, RE Schapire Journal of computer and system sciences 55 1, Arcing Classifiers Leo Breiman Ecography 29 2, My profile My library Metrics Alerts. Automaticacquisition of salient grammar fragments for call – type classification.
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boosting-bazed An evaluation of statistical approaches. Topics Discussed in This Paper. Journal of machine learning research 4 Nov, This paper has highly influenced other papers. Showing of 1, extracted citations. Categorization Boosting machine learning. References Publications referenced by this paper. We describe in detail an implementation, called BoosTexter, of the new boosting algorithms for text categorization tasks.
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