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» Boosting and Hard-Core Sets
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CEAS
2007
Springer
14 years 1 months ago
Asymmetric Gradient Boosting with Application to Spam Filtering
In this paper, we propose a new asymmetric boosting method, Boosting with Different Costs. Traditional boosting methods assume the same cost for misclassified instances from di...
Jingrui He, Bo Thiesson
ICMCS
2009
IEEE
189views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Emotion recognition from speech VIA boosted Gaussian mixture models
Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...
WEBI
2010
Springer
13 years 5 months ago
Boosting Biomedical Entity Extraction by Using Syntactic Patterns for Semantic Relation Discovery
Biomedical entity extraction from unstructured web documents is an important task that needs to be performed in order to discover knowledge in the veterinary medicine domain. In ge...
Svitlana Volkova, Doina Caragea, William H. Hsu, J...
ML
2000
ACM
144views Machine Learning» more  ML 2000»
13 years 7 months ago
MultiBoosting: A Technique for Combining Boosting and Wagging
MultiBoosting is an extension to the highly successful AdaBoost technique for forming decision committees. MultiBoosting can be viewed as combining AdaBoost with wagging. It is abl...
Geoffrey I. Webb
FLAIRS
2006
13 years 8 months ago
Using Validation Sets to Avoid Overfitting in AdaBoost
AdaBoost is a well known, effective technique for increasing the accuracy of learning algorithms. However, it has the potential to overfit the training set because its objective i...
Tom Bylander, Lisa Tate