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HIS
2004
15 years 3 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...

Publication
334views
15 years 11 months ago
Rollout Sampling Approximate Policy Iteration
Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schem...
Christos Dimitrakakis, Michail G. Lagoudakis
DATAMINE
2008
112views more  DATAMINE 2008»
15 years 2 months ago
PRIE: a system for generating rulelists to maximize ROC performance
Rules are commonly used for classification because they are modular, intelligible and easy to learn. Existing work in classification rule learning assumes the goal is to produce ca...
Tom Fawcett
108
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ICALT
2006
IEEE
15 years 8 months ago
Improving the Quality of Discussion Forum discourses by Using an Internal Market
We describe an approach that attempts to improve the quality of discussion forum discussions and to reduce the cost of discussion forum support by prioritizing and structuring mes...
Alexei Tretiakov, Øyvind Smestad, Kinshuk
SLSFS
2005
Springer
15 years 7 months ago
Random Projection, Margins, Kernels, and Feature-Selection
Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as...
Avrim Blum