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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Journal of machine learning research 4 Nov, 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, Articles 1—20 Show more. Topics Discussed in This Paper.
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boosting-basdd Get my own profile Cited by View all All Since Citations h-index 75 54 iindex The boosting approach to machine learning: Reducing multiclass to binary: This “Cited by” count includes citations to the following articles in Scholar. Advances in neural information processing systems, Journal of computer and system sciences 55 1, Large margin classification using the perceptron algorithm Y Freund, RE Schapire Machine learning 37 3, From This Paper Figures, tables, and topics from this paper.
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BoosTexter: A Boosting-based System for Text Categorization
New articles related to this author’s research. We present results comparing the performance of BoosTexter and a number of other text-categorization algorithms on a variety of tasks. See our FAQ for additional information. Semantic Scholar estimates that this publication has 2, citations based on the available data.
Improved boosting algorithms using confidence-rated predictions RE Schapire, Y Singer Machine learning 37 3, Nonlinear estimation and classification, Skip to search form Skip to main content.
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