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» Efficient Model Selection for Kernel Logistic Regression
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BMCBI
2007
194views more  BMCBI 2007»
13 years 7 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
SDM
2008
SIAM
256views Data Mining» more  SDM 2008»
13 years 8 months ago
Graph Mining with Variational Dirichlet Process Mixture Models
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda, Kenichi Kurihara
AISADM
2005
Springer
14 years 27 days ago
Execution Engine of Meta-learning System for KDD in Multi-agent Environment
Meta-learning system for KDD is an open and evolving platform for efficient testing and intelligent recommendation of data mining process. Metalearning is adopted to automate the s...
Ping Luo, Qing He, Rui Huang, Fen Lin, Zhongzhi Sh...
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
13 years 11 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa
ESANN
2006
13 years 8 months ago
Classification by means of Evolutionary Response Surfaces
Abstract. Response surfaces are a powerful tool for both classification and regression as they are able to model many different phenomena and construct complex boundaries between c...
Rafael del Castillo Gomariz, Nicolás Garc&i...