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DATAMINE
1999
143views more  DATAMINE 1999»
15 years 2 months ago
Partitioning Nominal Attributes in Decision Trees
To find the optimal branching of a nominal attribute at a node in an L-ary decision tree, one is often forced to search over all possible L-ary partitions for the one that yields t...
Don Coppersmith, Se June Hong, Jonathan R. M. Hosk...
104
Voted
ICML
2005
IEEE
16 years 3 months ago
Predicting good probabilities with supervised learning
We examine the relationship between the predictions made by different learning algorithms and true posterior probabilities. We show that maximum margin methods such as boosted tre...
Alexandru Niculescu-Mizil, Rich Caruana
103
Voted
ISMIR
2005
Springer
132views Music» more  ISMIR 2005»
15 years 8 months ago
VOISE: Learning to Segregate Voices in Explicit and Implicit Polyphony
Finding multiple occurrences of themes and patterns in music can be hampered due to polyphonic textures. This is caused by the complexity of music that weaves multiple independent...
Phillip B. Kirlin, Paul E. Utgoff
126
Voted
AI
2002
Springer
15 years 2 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
PKDD
2009
Springer
196views Data Mining» more  PKDD 2009»
15 years 9 months ago
Causality Discovery with Additive Disturbances: An Information-Theoretical Perspective
We consider causally sufficient acyclic causal models in which the relationship among the variables is nonlinear while disturbances have linear effects, and show that three princi...
Kun Zhang, Aapo Hyvärinen