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KDD
2010
ACM
197views Data Mining» more  KDD 2010»
13 years 6 months ago
Semi-supervised feature selection for graph classification
The problem of graph classification has attracted great interest in the last decade. Current research on graph classification assumes the existence of large amounts of labeled tra...
Xiangnan Kong, Philip S. Yu
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 6 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu
BMCBI
2008
160views more  BMCBI 2008»
13 years 9 months ago
Feature selection environment for genomic applications
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....
Fabrício Martins Lopes, David Correa Martin...
ICPR
2002
IEEE
14 years 10 months ago
The Economics of Classification: Error vs. Complexity
Although usually classifier error is the main concern in publications, in real applications classifier evaluation complexity may play a large role as well. In this paper, a simple...
Dick de Ridder, Elzbieta Pekalska, Robert P. W. Du...
DMIN
2006
124views Data Mining» more  DMIN 2006»
13 years 10 months ago
Optimal Multi-class Classification with Principal Components
An approach to build a multi-class classifier is proposed in this paper. This approach consists of a derivation to show under which loss function an optimal classifier can be obtai...
Albert Hoang