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BMCBI
2010
132views more  BMCBI 2010»
15 years 6 months ago
Error margin analysis for feature gene extraction
Background: Feature gene extraction is a fundamental issue in microarray-based biomarker discovery. It is normally treated as an optimization problem of finding the best predictiv...
Chi Kin Chow, Hai Long Zhu, Jessica Lacy, Winston ...
FGR
2008
IEEE
153views Biometrics» more  FGR 2008»
16 years 18 days ago
Facial image analysis using local feature adaptation prior to learning
Many facial image analysis methods rely on learningbased techniques such as Adaboost or SVMs to project classifiers based on the selection of local image filters (e.g., Haar and...
Rogerio Feris, Ying-li Tian, Yun Zhai, Arun Hampap...
ICIP
2003
IEEE
16 years 7 months ago
Face description based on decomposition and combining of a facial space with LDA
We propose a method of efficient face description for facial image retrieval from a large data set. The novel descriptor is obtained by decomposing the face image into several com...
Tae-Kyun Kim, Hyunwoo Kim, Wonjun Hwang, Seok-Cheo...
KDD
2004
ACM
302views Data Mining» more  KDD 2004»
16 years 6 months ago
Redundancy based feature selection for microarray data
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Lei Yu, Huan Liu
149
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TKDE
2010
168views more  TKDE 2010»
15 years 4 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...