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RSCTC
2000
Springer
151views Fuzzy Logic» more  RSCTC 2000»
13 years 11 months ago
Anytime Algorithm for Feature Selection
Feature selection is used to improve performance of learning algorithms by finding a minimal subset of relevant features. Since the process of feature selection is computationally ...
Mark Last, Abraham Kandel, Oded Maimon, Eugene Ebe...
ANNES
1995
13 years 11 months ago
The Development of Holte's 1R Classifier
The 1R procedure for machine learning is a very simple one that proves surprisingly effective on the standard datasets commonly used for evaluation. This paper describes the metho...
Craig G. Nevill-Manning, Geoffrey Holmes, Ian H. W...
CHI
1995
ACM
13 years 11 months ago
Pointing the Way: Active Collaborative Filtering
Collaborative filtering is based on the premise that people looking for information should be able to make use of what others have already found and evaluated. Current collaborati...
David Maltz, Kate Ehrlich
EURODAC
1995
IEEE
137views VHDL» more  EURODAC 1995»
13 years 11 months ago
A formal non-heuristic ATPG approach
This paper presents a formal approach to test combinational circuits. For the sake of explanation we describe the basic algorithms with the help of the stuck–at fault model. Ple...
Manfred Henftling, Hannes C. Wittmann, Kurt Antrei...
KDD
1995
ACM
133views Data Mining» more  KDD 1995»
13 years 11 months ago
Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology
In the wrapperapproachto feature subset selection, a searchfor an optimalset of features is madeusingthe induction algorithm as a black box. Theestimated future performanceof the ...
Ron Kohavi, Dan Sommerfield