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» An Experimental Study on Feature Subset Selection Methods
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KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 7 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
ICDAR
2011
IEEE
14 years 3 months ago
Comparative Study of Part-Based Handwritten Character Recognition Methods
—The purpose of this paper is to introduce three part-based methods for handwritten character recognition and then compare their performances experimentally. All of those methods...
Wang Song, Seiichi Uchida, Marcus Liwicki
ARTMED
2007
347views more  ARTMED 2007»
15 years 4 months ago
A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature
Objective: This study investigates the use of automated pattern recognition methods on magnetic resonance data with the ultimate goal to assist clinicians in the diagnosis of brai...
Jan Luts, Arend Heerschap, Johan A. K. Suykens, Sa...
BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
15 years 4 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
SEAL
1998
Springer
15 years 8 months ago
Genetic Programming with Active Data Selection
Genetic programming evolves Lisp-like programs rather than fixed size linear strings. This representational power combined with generality makes genetic programming an interesting ...
Byoung-Tak Zhang, Dong-Yeon Cho