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» Ensemble Methods in Machine Learning
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ICML
2001
IEEE
14 years 9 months ago
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers
Accurate, well-calibrated estimates of class membership probabilities are needed in many supervised learning applications, in particular when a cost-sensitive decision must be mad...
Bianca Zadrozny, Charles Elkan
ICALT
2005
IEEE
14 years 2 months ago
Multi-Learner System towards an Efficient E-Learning System
Existing multi-learner systems support three areas of group collaborative E-learning environments: communication, coordination, and collaboration. This distinction reflects the de...
Mohammed Abdel Razek, Claude Frasson, Marc Kaltenb...
ECTEL
2006
Springer
14 years 2 days ago
Emergent Knowledge Artifacts for Supporting Trialogical E-Learning
Abstract. This paper elaborates on scenarios for collaborative knowledge creation in the spirit of the trialogical learning paradigm. According to these scenarios the group knowled...
Yannis Tzitzikas, Vassilis Christophides, Giorgos ...
ICML
1991
IEEE
13 years 12 months ago
Constructive Induction in Knowledge-Based Neural Networks
Artificial neural networks have proven to be a successful, general method for inductive learning from examples. However, they have not often been viewed in terms of constructive ...
Geoffrey G. Towell, Mark Craven, Jude W. Shavlik
ML
2008
ACM
146views Machine Learning» more  ML 2008»
13 years 8 months ago
Improving maximum margin matrix factorization
Abstract. Collaborative filtering is a popular method for personalizing product recommendations. Maximum Margin Matrix Factorization (MMMF) has been proposed as one successful lear...
Markus Weimer, Alexandros Karatzoglou, Alex J. Smo...