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195
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GECCO
2005
Springer
16 years 14 days ago
2005
Springer
Identification of those genes that might anticipate the clinical behavior of different types of cancers is challenging due to availability of a smaller number of patient samples...
222
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MLDM
2005
Springer
16 years 13 days ago
2005
Springer
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
187
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COLT
2001
Springer
15 years 11 months ago
2001
Springer
In this paper we study a paradigm to generalize online classification algorithms for binary classification problems to multiclass problems. The particular hypotheses we investig...
196
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COLT
1999
Springer
15 years 11 months ago
1999
Springer
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
221
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COLT
1993
Springer
15 years 11 months ago
1993
Springer
The Vapnik-Chervonenkis (V-C) dimension is an important combinatorial tool in the analysis of learning problems in the PAC framework. For polynomial learnability, we seek upper bou...