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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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126
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ISCIS
2005
Springer
15 years 6 months ago
Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks
Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...
Zeki Erdem, Robi Polikar, Nejat Yumusak, Fikret S....
101
Voted
JAIR
2010
131views more  JAIR 2010»
14 years 11 months ago
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Jia-Hong Wu, Robert Givan
ISDA
2010
IEEE
14 years 10 months ago
Comparing SVM ensembles for imbalanced datasets
Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...
Vasudha Bhatnagar, Manju Bhardwaj, Ashish Mahabal
129
Voted
ECML
2005
Springer
15 years 6 months ago
Natural Actor-Critic
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
Jan Peters, Sethu Vijayakumar, Stefan Schaal
128
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JMLR
2010
162views more  JMLR 2010»
14 years 7 months ago
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design
An exceedingly large number of scientific and engineering fields are confronted with the need for computer simulations to study complex, real world phenomena or solve challenging ...
Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom D...