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EWCBR
2006
Springer
13 years 11 months ago
Rough Set Feature Selection Algorithms for Textual Case-Based Classification
Feature selection algorithms can reduce the high dimensionality of textual cases and increase case-based task performance. However, conventional algorithms (e.g., information gain)...
Kalyan Moy Gupta, David W. Aha, Philip Moore
ICASSP
2009
IEEE
14 years 2 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...
ICPR
2008
IEEE
14 years 8 months ago
Selecting relevant features for human motion recognition
Recently, there is a growing interest in automatic recognition of human motion for applications, such as humanoid robots, human activity monitoring, and surveillance. In this pape...
Dirk Gehrig, Tanja Schultz
ICIP
2006
IEEE
14 years 9 months ago
Perceptual Feature Selection for Semantic Image Classification
Content-based image retrieval has become an indispensable tool for managing the rapidly growing collections of digital images. The goal is to organize the contents semantically, a...
Dejan Depalov, Thrasyvoulos N. Pappas, Dongge Li, ...
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 5 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