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BMCBI
2005
131views more  BMCBI 2005»
14 years 9 months ago
Regularized Least Squares Cancer Classifiers from DNA microarray data
Background: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information ...
Nicola Ancona, Rosalia Maglietta, Annarita D'Addab...
KDD
2003
ACM
195views Data Mining» more  KDD 2003»
15 years 10 months ago
Visualizing changes in the structure of data for exploratory feature selection
Using visualization techniques to explore and understand high-dimensional data is an efficient way to combine human intelligence with the immense brute force computation power ava...
Elias Pampalk, Werner Goebl, Gerhard Widmer
MVA
2000
234views Computer Vision» more  MVA 2000»
14 years 9 months ago
An automatic assessment scheme for steel quality inspection
This paper presents an automatic system for steel quality assessment, by measuring textural properties of carbide distributions. In current steel inspection, specially etched and p...
Klaus Wiltschi, Axel Pinz, Tony Lindeberg
JMLR
2010
104views more  JMLR 2010»
14 years 4 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic
CIBCB
2005
IEEE
15 years 3 months ago
Feature Selection for Microarray Data Using Least Squares SVM and Particle Swarm Optimization
Feature selection is an important preprocessing technique for many pattern recognition problems. When the number of features is very large while the number of samples is relatively...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao