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» Bayesian Methods for Support Vector Machines: Evidence and P...
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KDD
2005
ACM
168views Data Mining» more  KDD 2005»
14 years 9 months ago
Nomograms for visualizing support vector machines
We propose a simple yet potentially very effective way of visualizing trained support vector machines. Nomograms are an established model visualization technique that can graphica...
Aleks Jakulin, Martin Mozina, Janez Demsar, Ivan B...
BMCBI
2007
142views more  BMCBI 2007»
13 years 8 months ago
Support Vector Machine-based method for predicting subcellular localization of mycobacterial proteins using evolutionary informa
Background: In past number of methods have been developed for predicting subcellular location of eukaryotic, prokaryotic (Gram-negative and Gram-positive bacteria) and human prote...
Mamoon Rashid, Sudipto Saha, Gajendra P. S. Raghav...
ESANN
2006
13 years 10 months ago
Evolino for recurrent support vector machines
Abstract. We introduce a new class of recurrent, truly sequential SVM-like devices with internal adaptive states, trained by a novel method called EVOlution of systems with KErnel-...
Jürgen Schmidhuber, Matteo Gagliolo, Daan Wie...
JCDL
2003
ACM
160views Education» more  JCDL 2003»
14 years 1 months ago
Automatic Document Metadata Extraction Using Support Vector Machines
Automatic metadata generation provides scalability and usability for digital libraries and their collections. Machine learning methods offer robust and adaptable automatic metadat...
Hui Han, C. Lee Giles, Eren Manavoglu, Hongyuan Zh...
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...