Abstract
We present a text classification method based upon maximum entropy optimization. Having a set of documents which must be classified into some given classes, a maximum entropy optimization problem is considered. In order to solve this problem, we consider its Lagrange dual and we derive, by means of strong duality, the optimality conditions.
After solving the dual problem, we obtain, as solution of the primal problem, a distribution of probabilities representing the chances of the documents to belong to each class.
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© 2003 Deutscher Universitäts-Verlag/GWV Fachverlage GmbH, Wiesbaden
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Boţ, R.I., Grad, SM., Wanka, G. (2003). Maximum entropy optimization for text classification problems. In: Habenicht, W., Scheubrein, B., Scheubrein, R. (eds) Multi-Criteria- und Fuzzy-Systeme in Theorie und Praxis. Deutscher Universitätsverlag. https://doi.org/10.1007/978-3-322-81539-2_13
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DOI: https://doi.org/10.1007/978-3-322-81539-2_13
Publisher Name: Deutscher Universitätsverlag
Print ISBN: 978-3-8244-7864-4
Online ISBN: 978-3-322-81539-2
eBook Packages: Springer Book Archive