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BMCBI
2007
178views more  BMCBI 2007»
13 years 7 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
KDD
2003
ACM
142views Data Mining» more  KDD 2003»
14 years 8 months ago
Frequent-subsequence-based prediction of outer membrane proteins
A number of medically important disease-causing bacteria (collectively called Gram-negative bacteria) are noted for the extra "outer" membrane that surrounds their cell....
Rong She, Fei Chen 0002, Ke Wang, Martin Ester, Je...
KDD
2008
ACM
167views Data Mining» more  KDD 2008»
14 years 8 months ago
A sequential dual method for large scale multi-class linear svms
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as w...
S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang...
BMCBI
2010
243views more  BMCBI 2010»
13 years 7 months ago
Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
Christoph Bartenhagen, Hans-Ulrich Klein, Christia...
KES
2008
Springer
13 years 7 months ago
Downsizing Multigenic Predictors of the Response to Preoperative Chemotherapy in Breast Cancer
We present a method for designing efficient multigenic predictors with few probes and its application to the prediction of the response to preoperative chemotherapy in breast cance...
René Natowicz, Roberto Incitti, Roman Rouzi...