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...
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...
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...
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...
In the wrapperapproachto feature subset selection, a searchfor an optimalset of features is madeusingthe induction algorithm as a black box. Theestimated future performanceof the ...