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» Data Mining via Support Vector Machines
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MLDM
2007
Springer
15 years 10 months ago
Applying Frequent Sequence Mining to Identify Design Flaws in Enterprise Software Systems
In this paper we show how frequent sequence mining (FSM) can be applied to data produced by monitoring distributed enterprise applications. In particular we show how we applied FSM...
Trevor Parsons, John Murphy, Patrick O'Sullivan
HAIS
2009
Springer
15 years 9 months ago
Incremental Kernel Machines for Protein Remote Homology Detection
Abstract. Protein membership prediction is a fundamental task to retrieve information for unknown or unidentified sequences. When support vector machines (SVMs) are associated with...
Lionel Morgado, Carlos Pereira
IJCAI
2007
15 years 6 months ago
Detection of Cognitive States from fMRI Data Using Machine Learning Techniques
Over the past decade functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful technique to locate activity of human brain while engaged in a particular task or cogni...
Vishwajeet Singh, Krishna P. Miyapuram, Raju S. Ba...
ICCV
2003
IEEE
16 years 6 months ago
Machine Learning and Multiscale Methods in the Identification of Bivalve Larvae
This paper describes a novel application of support vector machines and multiscale texture and color invariants to a problem in biological oceanography: the identification of 6 sp...
Sanjay Tiwari, Scott Gallager
BMCBI
2006
146views more  BMCBI 2006»
15 years 4 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara