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» Anomaly Detection Through a Bayesian Support Vector Machine
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IJCNN
2006
IEEE
14 years 2 months ago
Sparse Bayesian Models: Bankruptcy-Predictors of Choice?
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
Bernardete Ribeiro, Armando Vieira, João Ca...
WCE
2007
13 years 9 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
KDD
2007
ACM
202views Data Mining» more  KDD 2007»
14 years 9 months ago
Support feature machine for classification of abnormal brain activity
In this study, a novel multidimensional time series classification technique, namely support feature machine (SFM), is proposed. SFM is inspired by the optimization model of suppo...
Wanpracha Art Chaovalitwongse, Ya-Ju Fan, Rajesh C...
SWARM
2010
SPRINGER
154views Optimization» more  SWARM 2010»
13 years 7 months ago
An Immune Concentration Based Virus Detection Approach Using Particle Swarm Optimization
This paper proposes an immune concentration based virus detection approach which utilizes a two-element concentration vector to construct the feature. In this approach, ‘self’ ...
Wei Wang, Pengtao Zhang, Ying Tan
AIRWEB
2008
Springer
13 years 10 months ago
Web spam identification through content and hyperlinks
We present an algorithm, witch, that learns to detect spam hosts or pages on the Web. Unlike most other approaches, it simultaneously exploits the structure of the Web graph as we...
Jacob Abernethy, Olivier Chapelle, Carlos Castillo