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KDD
2002
ACM
160views Data Mining» more  KDD 2002»
16 years 1 months ago
Scaling multi-class support vector machines using inter-class confusion
Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...
Shantanu Godbole, Sunita Sarawagi, Soumen Chakraba...
83
Voted
ECML
2006
Springer
15 years 4 months ago
Right of Inference: Nearest Rectangle Learning Revisited
In Nearest Rectangle (NR) learning, training instances are generalized into hyperrectangles and a query is classified according to the class of its nearest rectangle. The method ha...
Byron J. Gao, Martin Ester
73
Voted
ICML
2005
IEEE
16 years 1 months ago
PAC-Bayes risk bounds for sample-compressed Gibbs classifiers
We extend the PAC-Bayes theorem to the sample-compression setting where each classifier is represented by two independent sources of information: a compression set which consists ...
François Laviolette, Mario Marchand
101
Voted
ICML
2010
IEEE
15 years 1 months ago
Supervised Aggregation of Classifiers using Artificial Prediction Markets
Prediction markets are used in real life to predict outcomes of interest such as presidential elections. In this work we introduce a mathematical theory for Artificial Prediction ...
Nathan Lay, Adrian Barbu
120
Voted
ICPR
2004
IEEE
16 years 1 months ago
A Consistency-Based Model Selection for One-Class Classification
Model selection in unsupervised learning is a hard problem. In this paper a simple selection criterion for hyperparameters in one-class classifiers (OCCs) is proposed. It makes us...
David M. J. Tax, Klaus-Robert Müller