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» Choosing Multiple Parameters for Support Vector Machines
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PKDD
2009
Springer
113views Data Mining» more  PKDD 2009»
14 years 2 months ago
Feature Selection for Density Level-Sets
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an eï¬...
Marius Kloft, Shinichi Nakajima, Ulf Brefeld
CONTEXT
2007
Springer
14 years 2 months ago
Risk Context Effects in Inductive Reasoning: An Experimental and Computational Modeling Study
Mechanisms that underlie the inductive reasoning process in risk contexts are investigated. Experimental results indicate that people rate the same inductive reasoning argument dif...
Kayo Sakamoto, Masanori Nakagawa
ICMLA
2007
13 years 9 months ago
Automatic medical coding of patient records via weighted ridge regression
In this paper, we apply weighted ridge regression to tackle the highly unbalanced data issue in automatic largescale ICD-9 coding of medical patient records. Since most of the ICD...
Jian-Wu Xu, Shipeng Yu, Jinbo Bi, Lucian Vlad Lita...
ESANN
2006
13 years 9 months ago
Degeneracy in model selection for SVMs with radial Gaussian kernel
We consider the model selection problem for support vector machines applied to binary classification. As the data generating process is unknown, we have to rely on heuristics as mo...
Tobias Glasmachers
ICCTA
2007
IEEE
13 years 8 months ago
Digital Signal Types Identification Using a Hierarchical SVM-Based Classifier and Efficient Features
Automatic digital signal type identification (ADSTI) is an important topic for both military and civilian communication applications. Most of proposed techniques (identifiers) can...
Ataollah Ebrahimzadeh, Seyed Alireza Seyedin