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» Memetic Algorithms for Feature Selection on Microarray Data
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HICSS
2009
IEEE
101views Biometrics» more  HICSS 2009»
14 years 2 months ago
Building a Better Similarity Trap with Statistically Improbable Features
One of the persistent topics in digital forensic research in recent years has been the problem of finding all things similar. Developed tools usually take on the form of similarit...
Vassil Roussev
BMCBI
2006
94views more  BMCBI 2006»
13 years 7 months ago
Noise-injected neural networks show promise for use on small-sample expression data
Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
Jianping Hua, James Lowey, Zixiang Xiong, Edward R...
ICPR
2004
IEEE
14 years 8 months ago
Robust Feature Matching Across Widely Separated Color Images
We present a novel method for feature matching across widely separated color images. The proposed approach is robust and can support various correspondence based algorithms e.g. t...
Alexander Kaplan, Ehud Rivlin, Ilan Shimshoni
ICANN
2001
Springer
14 years 5 days ago
Feature Extraction Using ICA
In manipulating data such as in supervised learning, we often extract new features from original features for the purpose of reducing the dimensions of feature space and achieving ...
Nojun Kwak, Chong-Ho Choi, Jin-Young Choi
ICML
2007
IEEE
14 years 8 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...