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,...
Feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier perfo...
Feature selection is a problem of choosing a subset of relevant features. Researchers have been searching for optimal feature selection methods. `Branch and Bound' and Focus a...
The study described in this paper, analyzed the urban and suburban air pollution principal causes and identified the best subset of features (meteorological data and air pollutants...
Giovanni Raimondo, Alfonso Montuori, Walter Moniac...
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...