The Multilevel Classification Problem and a Monotonicity Hint
Identifieur interne : 000410 ( Main/Exploration ); précédent : 000409; suivant : 000411The Multilevel Classification Problem and a Monotonicity Hint
Auteurs : Malik Magdon-Ismail [États-Unis] ; Justin Chen [États-Unis] ; S. Abu-Mostafa [États-Unis]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2002.
Abstract
Abstract: We introduce and formalize the multilevel classification problem, in which each category can be subdivided into different levels. We analyze the framework in a Bayesian setting using Normal class conditional densities. Within this framework, a natural monotonicity hint converts the problem into a nonlinear programming task, with non-linear constraints. We present Monte Carlo and gradient based techniques for addressing this task, and show the results of simulations. Incorporation of monotonicity yields a systematic improvement in performance.
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DOI: 10.1007/3-540-45675-9_61
Affiliations:
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