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» Machine Learning with Data Dependent Hypothesis Classes
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78
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TNN
2008
133views more  TNN 2008»
14 years 11 months ago
A General Wrapper Approach to Selection of Class-Dependent Features
In this paper, we argue that for a C-class classification problem, C 2-class classifiers, each of which discriminating one class from the other classes and having a characteristic ...
Lipo Wang, Nina Zhou, Feng Chu
101
Voted
ECML
2005
Springer
15 years 5 months ago
Fitting the Smallest Enclosing Bregman Ball
Finding a point which minimizes the maximal distortion with respect to a dataset is an important estimation problem that has recently received growing attentions in machine learnin...
Richard Nock, Frank Nielsen
ML
2002
ACM
133views Machine Learning» more  ML 2002»
14 years 11 months ago
Estimating Generalization Error on Two-Class Datasets Using Out-of-Bag Estimates
For two-class datasets, we provide a method for estimating the generalization error of a bag using out-of-bag estimates. In bagging, each predictor (single hypothesis) is learned ...
Tom Bylander
102
Voted
NN
1998
Springer
108views Neural Networks» more  NN 1998»
14 years 11 months ago
How embedded memory in recurrent neural network architectures helps learning long-term temporal dependencies
Learning long-term temporal dependencies with recurrent neural networks can be a difficult problem. It has recently been shown that a class of recurrent neural networks called NA...
Tsungnan Lin, Bill G. Horne, C. Lee Giles
EXPERT
1998
83views more  EXPERT 1998»
14 years 11 months ago
Data-Driven Constructive Induction
Constructive induction divides the problem of learning an inductive hypothesis into two intertwined searches: one—for the “best” representation space, and two—for the “be...
Eric Bloedorn, Ryszard S. Michalski