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» Scaling-Up Support Vector Machines Using Boosting Algorithm
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151
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AICS
2009
15 years 5 days ago
Analysis of the Effect of Unexpected Outliers in the Classification of Spectroscopy Data
Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume all classes are characte...
Frank G. Glavin, Michael G. Madden
BIBE
2001
IEEE
15 years 6 months ago
Gene Classification using Expression Profiles: A Feasibility Study
As various genome sequencing projects have already been completed or are near completion, genome researchers are shifting their focus from structural genomics to functional genomi...
Michihiro Kuramochi, George Karypis
118
Voted
ICML
2005
IEEE
16 years 3 months ago
Large scale genomic sequence SVM classifiers
In genomic sequence analysis tasks like splice site recognition or promoter identification, large amounts of training sequences are available, and indeed needed to achieve suffici...
Bernhard Schölkopf, Gunnar Rätsch, S&oum...
CORR
2010
Springer
104views Education» more  CORR 2010»
15 years 2 months ago
Empirical learning aided by weak domain knowledge in the form of feature importance
Standard hybrid learners that use domain knowledge require stronger knowledge that is hard and expensive to acquire. However, weaker domain knowledge can benefit from prior knowle...
Ridwan Al Iqbal
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 2 months ago
Local decomposition for rare class analysis
Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
Junjie Wu, Hui Xiong, Peng Wu, Jian Chen