Machine Learning, ECML- ...: ProceedingsSpringer, 2004 - Induction (Logic) |
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Contents
Invited Papers | 1 |
RealWorld Learning with Markov Logic Networks | 17 |
Applying Support Vector Machines to Imbalanced Datasets | 39 |
Copyright | |
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Common terms and phrases
accuracy action agent algorithm analysis answer applied approach approximation attributes average better called classification clusters combination common compared complexity compute concept conditional Conference considered covered dataset decision trees defined denotes depends described distance distribution domain effect equation error estimate evaluation examples experiments extraction Figure filter function given graph improve increase induction input instances International Italy kernel labels linear Machine Learning matrix means measure messages method naive Bayes negative node Note obtained operator optimal pairs parameters performance positive possible prediction present probability problem Proceedings proposed random ranking reduced References regression representation represents requires respectively reward rule sample selection shown similar space standard statistics step Table task trees variables vector weighted
Bibliographic information
| Title | Machine Learning, ECML- ...: Proceedings Lecture notes in computer science Lecture notes in computer science: Lecture notes in artificial intelligence |
| Publisher | Springer, 2004 |
| Original from | the University of Michigan |
| Digitized | Nov 15, 2007 |
| ISBN | 3540231056, 9783540231059 |
| Export Citation | BiBTeX EndNote RefMan |