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» Learning to learn with the informative vector machine
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ESANN
2006
15 years 6 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
MOBISYS
2008
ACM
16 years 4 months ago
Behavioral detection of malware on mobile handsets
A novel behavioral detection framework is proposed to detect mobile worms, viruses and Trojans, instead of the signature-based solutions currently available for use in mobile devi...
Abhijit Bose, Xin Hu, Kang G. Shin, Taejoon Park
BMCBI
2006
142views more  BMCBI 2006»
15 years 4 months ago
Improving the Performance of SVM-RFE to Select Genes in Microarray Data
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
Yuanyuan Ding, Dawn Wilkins
147
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ICDCS
2002
IEEE
15 years 9 months ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
GECCO
2007
Springer
159views Optimization» more  GECCO 2007»
15 years 10 months ago
Evolutionary hypernetwork models for aptamer-based cardiovascular disease diagnosis
We present a biology-inspired probabilistic graphical model, called the hypernetwork model, and its application to medical diagnosis of disease. The hypernetwork models are a way ...
JungWoo Ha, Jae-Hong Eom, Sung-Chun Kim, Byoung-Ta...