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JSW
2016
61views more  JSW 2016»
4 years 1 months ago
Handling Sparse Data Sets by Applying Contrast Set Mining in Feature Selection
—A data set is sparse if the number of samples in a data set is not sufficient to model the data accurately. Recent research emphasized interest in applying data mining and featu...
Dijana Oreski, Mario Konecki
KDD
2001
ACM
192views Data Mining» more  KDD 2001»
10 years 6 months ago
Data mining with sparse grids using simplicial basis functions
Recently we presented a new approach [18] to the classification problem arising in data mining. It is based on the regularization network approach but, in contrast to other method...
Jochen Garcke, Michael Griebel
SDM
2008
SIAM
117views Data Mining» more  SDM 2008»
9 years 7 months ago
A Feature Selection Algorithm Capable of Handling Extremely Large Data Dimensionality
With the advent of high throughput technologies, feature selection has become increasingly important in a wide range of scientific disciplines. We propose a new feature selection ...
Yijun Sun, Sinisa Todorovic, Steve Goodison
ICANN
2009
Springer
9 years 3 months ago
Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data
Different algorithms have been proposed in the literature to cluster gene expression data, however there is no single algorithm that can be considered the best one independently on...
André C. A. Nascimento, Ricardo Bastos Cava...
IDA
2002
Springer
9 years 5 months ago
Classification with sparse grids using simplicial basis functions
Recently we presented a new approach [20] to the classification problem arising in data mining. It is based on the regularization network approach but in contrast to other methods...
Jochen Garcke, Michael Griebel
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