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» Distance Measure Assisted Rough Set Feature Selection
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FUZZIEEE
2007
IEEE
13 years 11 months ago
Distance Measure Assisted Rough Set Feature Selection
Abstract— Feature Selection (FS) is a technique for dimensionality reduction. Its aims are to select a subset of the original features of a dataset which are rich in the most use...
Neil MacParthalain, Qiang Shen, Richard Jensen
KBS
2008
98views more  KBS 2008»
13 years 3 months ago
Mixed feature selection based on granulation and approximation
Feature subset selection presents a common challenge for the applications where data with tens or hundreds of features are available. Existing feature selection algorithms are mai...
Qinghua Hu, Jinfu Liu, Daren Yu
ICCBR
2007
Springer
13 years 11 months ago
Catching the Drift: Using Feature-Free Case-Based Reasoning for Spam Filtering
In this paper, we compare case-based spam filters, focusing on their resilience to concept drift. In particular, we evaluate how to track concept drift using a case-based spam fi...
Sarah Jane Delany, Derek G. Bridge
CBMS
2009
IEEE
13 years 11 months ago
Comparative study of spine vertebra shape retrieval using learning-based feature selection
Feature extraction and selection are two important steps for shape retrieval. Given a data set, a set of features which describe the shape property from different aspects are extr...
Haiying Guan, Sameer Antani, L. Rodney Long, Georg...
ISDA
2009
IEEE
13 years 11 months ago
Clustering-Based Feature Selection in Semi-supervised Problems
— In this contribution a feature selection method in semi-supervised problems is proposed. This method selects variables using a feature clustering strategy, using a combination ...
Ianisse Quinzán, José Manuel Sotoca,...