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» Learning DNF by Decision Trees
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ICML
2004
IEEE
15 years 10 months ago
Decision trees with minimal costs
We propose a simple, novel and yet effective method for building and testing decision trees that minimizes the sum of the misclassification and test costs. More specifically, we f...
Charles X. Ling, Qiang Yang, Jianning Wang, Shicha...
ICASSP
2008
IEEE
15 years 4 months ago
Effective error prediction using decision tree for ASR grammar network in call system
CALL (Computer Assisted Language Learning) systems using ASR (Automatic Speech Recognition) for second language learning have received increasing interest recently. However, it st...
Hongcui Wang, Tatsuya Kawahara
ISM
2005
IEEE
138views Multimedia» more  ISM 2005»
15 years 3 months ago
Investigation of Combining SVM and Decision Tree for Emotion Classification
This paper discusses the use of a combination of support vector machine and decision tree learning for recognizing four emotions in speech, which are Neutral, Angry, Lombard, and ...
Thao Nguyen, Mingkun Li, Iris Bass, Ishwar K. Seth...
ICML
2005
IEEE
15 years 10 months ago
Why skewing works: learning difficult Boolean functions with greedy tree learners
We analyze skewing, an approach that has been empirically observed to enable greedy decision tree learners to learn "difficult" Boolean functions, such as parity, in the...
Bernard Rosell, Lisa Hellerstein, Soumya Ray, Davi...
AAAI
2006
14 years 11 months ago
Decision Tree Methods for Finding Reusable MDP Homomorphisms
straction is a useful tool for agents interacting with environments. Good state abstractions are compact, reuseable, and easy to learn from sample data. This paper and extends two...
Alicia P. Wolfe, Andrew G. Barto