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» Feature Subset Selection and Ranking for Data Dimensionality...
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SSPR
2004
Springer
15 years 7 months ago
Feature Shaving for Spectroscopic Data
High-resolution spectroscopy is a powerful industrial tool. The number of features (wavelengths) in these data sets varies from several hundreds up to a thousand. Relevant feature ...
Serguei Verzakov, Pavel Paclík, Robert P. W...
ICML
2009
IEEE
15 years 8 months ago
Non-monotonic feature selection
We consider the problem of selecting a subset of m most informative features where m is the number of required features. This feature selection problem is essentially a combinator...
Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, ...
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RSFDGRC
2005
Springer
190views Data Mining» more  RSFDGRC 2005»
15 years 7 months ago
Finding Rough Set Reducts with SAT
Abstract. Feature selection refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encountered in many areas such as machine...
Richard Jensen, Qiang Shen, Andrew Tuson
AAAI
2010
15 years 3 months ago
Conformal Mapping by Computationally Efficient Methods
Dimensionality reduction is the process by which a set of data points in a higher dimensional space are mapped to a lower dimension while maintaining certain properties of these p...
Stefan Pintilie, Ali Ghodsi
PRL
2007
180views more  PRL 2007»
15 years 1 months ago
Feature selection based on rough sets and particle swarm optimization
: We propose a new feature selection strategy based on rough sets and Particle Swarm Optimization (PSO). Rough sets has been used as a feature selection method with much success, b...
Xiangyang Wang, Jie Yang, Xiaolong Teng, Weijun Xi...