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» A supervised learning approach for imbalanced data sets
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ISCI
2008
166views more  ISCI 2008»
15 years 4 months ago
A discretization algorithm based on Class-Attribute Contingency Coefficient
Discretization algorithms have played an important role in data mining and knowledge discovery. They not only produce a concise summarization of continuous attributes to help the ...
Cheng-Jung Tsai, Chien-I Lee, Wei-Pang Yang
TREC
2007
15 years 5 months ago
Relaxed Online SVMs in the TREC Spam Filtering Track
Relaxed Online Support Vector Machines (ROSVMs) have recently been proposed as an efficient methodology for attaining an approximate SVM solution for streaming data such as the on...
David Sculley, Gabriel Wachman
KDD
2009
ACM
150views Data Mining» more  KDD 2009»
16 years 5 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
BMCBI
2007
143views more  BMCBI 2007»
15 years 4 months ago
Gene selection for classification of microarray data based on the Bayes error
Background: With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, ...
Ji-Gang Zhang, Hong-Wen Deng
GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
15 years 8 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard