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» Training Data Selection for Support Vector Machines
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FSKD
2007
Springer
98views Fuzzy Logic» more  FSKD 2007»
14 years 3 months ago
Learning Selective Averaged One-Dependence Estimators for Probability Estimation
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
Qing Wang, Chuan-hua Zhou, Jiankui Guo
ICML
2009
IEEE
14 years 10 months ago
Semi-supervised learning using label mean
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
BMCBI
2008
93views more  BMCBI 2008»
13 years 9 months ago
Hybrid MM/SVM structural sensors for stochastic sequential data
In this paper we present preliminary results stemming from a novel application of Markov Models and Support Vector Machines to splice site classification of Intron-Exon and Exon-I...
Brian Roux, Stephen Winters-Hilt
ISMIR
2005
Springer
175views Music» more  ISMIR 2005»
14 years 2 months ago
A Classification Approach to Melody Transcription
Melodies provide an important conceptual summarization of polyphonic audio. The extraction of melodic content has practical applications ranging from content-based audio retrieval...
Graham E. Poliner, Daniel P. W. Ellis
ICDM
2005
IEEE
179views Data Mining» more  ICDM 2005»
14 years 2 months ago
Bagging with Adaptive Costs
Ensemble methods have proved to be highly effective in improving the performance of base learners under most circumstances. In this paper, we propose a new algorithm that combine...
Yi Zhang, W. Nick Street