Machine Learning, ECML- ...: ProceedingsSpringer, 2004 - Induction (Logic) |
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Page 50
... Machine Studies , 36 , 267-287 . 2. Chawla , N. , Bowyer , K. , Hall , L ... Machine Learning Research , 1 . 5. Cristianini , N. & Shawe - Taylor , J. ( 2000 ) ... Conference on Artificial Intelligence : Special Track on Inductive Learning ...
... Machine Studies , 36 , 267-287 . 2. Chawla , N. , Bowyer , K. , Hall , L ... Machine Learning Research , 1 . 5. Cristianini , N. & Shawe - Taylor , J. ( 2000 ) ... Conference on Artificial Intelligence : Special Track on Inductive Learning ...
Page 133
... Conference on Machine Learning ( ECML - 94 ) , volume 784 of Lecture Notes in Artificial Intelligence , pages 122-137 , Catania , Italy , 1994 . Springer - Verlag . [ 6 ] Johannes Fürnkranz . Pruning algorithms for rule learning . Machine ...
... Conference on Machine Learning ( ECML - 94 ) , volume 784 of Lecture Notes in Artificial Intelligence , pages 122-137 , Catania , Italy , 1994 . Springer - Verlag . [ 6 ] Johannes Fürnkranz . Pruning algorithms for rule learning . Machine ...
Page 512
... conference on Machine Learning . Morgan Kaufmann ( 2003 ) 416-423 7. Frank , E. , Trigg , L. , Holmes , G. , Witten , I. H .: Naive Bayes for Regression . Machine Learning 41 ( 1 ) ( 2000 ) 5-15 8. Friedman , N. , Greiger , D ...
... conference on Machine Learning . Morgan Kaufmann ( 2003 ) 416-423 7. Frank , E. , Trigg , L. , Holmes , G. , Witten , I. H .: Naive Bayes for Regression . Machine Learning 41 ( 1 ) ( 2000 ) 5-15 8. Friedman , N. , Greiger , D ...
Contents
Invited Papers | 1 |
RealWorld Learning with Markov Logic Networks | 17 |
Applying Support Vector Machines to Imbalanced Datasets | 39 |
Copyright | |
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accuracy agent analysis applied approach Artificial Intelligence attributes average Bayesian network Berlin Heidelberg 2004 Boulicaut CIPER CITree classification clusters combination compute concept Conference on Machine convergence cross-validation curve Data Mining database dataset decision trees defined denotes distribution domain dynamic ECML ECTD equation error evaluation experiments extraction filter Fisher kernels function approximators graph heuristic HEXQ hidden Markov models hyperplane induction input International Conference iteration kernel learner learning algorithms linear LNAI Machine Learning matrix measure messages method naive Bayes Neural node obtained one-class SVMs optimal overfitting pairs paper parameters performance polynomial positive examples prediction probability estimates problem Q-learning random random forests ranking regression reinforcement learning representation reward rule sample SDMs Section semi-supervised learning Springer-Verlag Berlin Heidelberg SSAIR statistics supervised learning support vector machines Table task tion training data training examples training set unlabeled value function variables