Machine Learning, ECML- ...: ProceedingsSpringer, 2000 - Induction (Logic) |
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Contents
ProcessOriented Evaluation | 3 |
ShortTerm Profiling for a CaseBased Reasoning | 23 |
Learning Trading Rules with Inductive Logic Programming | 39 |
Copyright | |
24 other sections not shown
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Common terms and phrases
accuracy algorithm analysis applied approach associated attributes average better boosting classifier clustering combination compared Computer concept considered construct contains corresponding cost database datasets decision tree defined described detection determine direct discretization distribution documents domain effect ensemble error error rate estimate evaluation event example expected experiments Figure frequent function given grammar important improve increase indicators induction input instance International knowledge labeled layer linear Machine Learning means measure method Mining neural nodes Note objects observed obtained partial patterns performance points possible prediction present probability problem procedure Proceedings proposed pruning random ranking reduce regression relations representation represented respect rules sample selection sequence shown shows significant similar space split step strategy Table task techniques update vector weight
Bibliographic information
| Title | Machine Learning, ECML- ...: Proceedings Lecture notes in computer science Lecture notes in computer science: Lecture notes in artificial intelligence |
| Publisher | Springer, 2000 |
| Original from | the University of Michigan |
| Digitized | Nov 15, 2007 |
| ISBN | 3540676023, 9783540676027 |
| Export Citation | BiBTeX EndNote RefMan |