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» Feature Selection Algorithms: A Survey and Experimental Eval...
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ICDM
2008
IEEE
107views Data Mining» more  ICDM 2008»
14 years 2 months ago
Graph-Based Iterative Hybrid Feature Selection
When the number of labeled examples is limited, traditional supervised feature selection techniques often fail due to sample selection bias or unrepresentative sample problem. To ...
ErHeng Zhong, Sihong Xie, Wei Fan, Jiangtao Ren, J...
KDD
2003
ACM
109views Data Mining» more  KDD 2003»
14 years 8 months ago
Experimental design for solicitation campaigns
Data mining techniques are routinely used by fundraisers to select those prospects from a large pool of candidates who are most likely to make a financial contribution. These tech...
Uwe F. Mayer, Armand Sarkissian
BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
13 years 8 months ago
What should be expected from feature selection in small-sample settings
Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
Chao Sima, Edward R. Dougherty
JVCIR
2006
126views more  JVCIR 2006»
13 years 7 months ago
Efficient intra- and inter-mode selection algorithms for H.264/ AVC
Intra-frame mode selection and inter-frame mode selection are new features introduced in the H.264 standard. Intra-frame mode selection dramatically reduces spatial redundancy in ...
Andy C. Yu, King Ngi Ngan, Graham R. Martin
JSAC
2010
146views more  JSAC 2010»
13 years 2 months ago
NLOS identification and mitigation for localization based on UWB experimental data
Abstract--Sensor networks can benefit greatly from locationawareness, since it allows information gathered by the sensors to be tied to their physical locations. Ultra-wide bandwid...
Stefano Maranò, Wesley M. Gifford, Henk Wym...