—Randomized testing is an effective method for testing software units. Thoroughness of randomized unit testing varies widely according to the settings of certain parameters, such...
Abstract. This paper addresses the problem of feature selection within classification processes. We present a comparison of a feature subset selection with respect to two boosting ...
In the wrapperapproachto feature subset selection, a searchfor an optimalset of features is madeusingthe induction algorithm as a black box. Theestimated future performanceof the ...
Feature subset selection has become more and more a common topic of research. This popularity is partly due to the growth in the number of features and application domains. The fa...
Abstract. A machine learning-based approach to the prediction of molecular bioactivity in new drugs is proposed. Two important aspects are considered for the task: feature subset s...
Abstract. The performance of classification algorithms in machine learning is affected by the features used to describe the labeled examples presented to the inducers. Therefore,...
Abstract. We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techn...
Most of the prior work in biometric literature has only emphasized on the issue of feature extraction and classification. However, the critical issue of examining the usefulness of...
In this paper we propose PARTfs which adopts a supervised machine learning algorithm, namely partial decision trees, as a method for feature subset selection. In particular, it is...