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» Classification of Ordinal Data
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132
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KDD
2010
ACM
197views Data Mining» more  KDD 2010»
15 years 14 days 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
133
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BMCBI
2008
157views more  BMCBI 2008»
15 years 2 months ago
Dimension reduction with redundant gene elimination for tumor classification
Background: Analysis of gene expression data for tumor classification is an important application of bioinformatics methods. But it is hard to analyse gene expression data from DN...
Xue-Qiang Zeng, Guo-Zheng Li, Jack Y. Yang, Mary Q...
BIBM
2008
IEEE
125views Bioinformatics» more  BIBM 2008»
15 years 4 months ago
On the Role of Local Matching for Efficient Semi-supervised Protein Sequence Classification
Recent studies in protein sequence analysis have leveraged the power of unlabeled data. For example, the profile and mismatch neighborhood kernels have shown significant improveme...
Pavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic
100
Voted
CVPR
2007
IEEE
16 years 4 months ago
Feature Mining for Image Classification
The efficiency and robustness of a vision system is often largely determined by the quality of the image features available to it. In data mining, one typically works with immense...
Piotr Dollár, Zhuowen Tu, Hai Tao, Serge Be...
NIPS
1990
15 years 3 months ago
Bumptrees for Efficient Function, Constraint and Classification Learning
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. A...
Stephen M. Omohundro