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» Feature selection in a kernel space
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ICML
2003
IEEE
14 years 8 months ago
Marginalized Kernels Between Labeled Graphs
A new kernel function between two labeled graphs is presented. Feature vectors are defined as the counts of label paths produced by random walks on graphs. The kernel computation ...
Hisashi Kashima, Koji Tsuda, Akihiro Inokuchi
IJON
2007
134views more  IJON 2007»
13 years 7 months ago
Analysis of SVM regression bounds for variable ranking
This paper addresses the problem of variable ranking for Support Vector Regression. The relevance criteria that we proposed are based on leave-one-out bounds and some variants and...
Alain Rakotomamonjy
AI
2009
Springer
14 years 2 months ago
An Iterative Hybrid Filter-Wrapper Approach to Feature Selection for Document Clustering
The manipulation of large-scale document data sets often involves the processing of a wealth of features that correspond with the available terms in the document space. The employm...
Mohammad-Amin Jashki, Majid Makki, Ebrahim Bagheri...
NIPS
2007
13 years 9 months ago
Hierarchical Penalization
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hiera...
Marie Szafranski, Yves Grandvalet, Pierre Morizet-...
ESWA
2007
151views more  ESWA 2007»
13 years 7 months ago
A novel feature selection algorithm for text categorization
With the development of the web, large numbers of documents are available on the Internet. Digital libraries, news sources and inner data of companies surge more and more. Automat...
Wenqian Shang, Houkuan Huang, Haibin Zhu, Yongmin ...