Correlation - Based and Contextual Merit - BasedEnsemble Feature

Recent research has proved the beneets of using an ensemble of diverse and accurate base classiiers for classiication problems. In this paper the focus is on producing diverse ensembles with the aid of three feature selection heuristics based on two approaches: correlation and contextual merit-based ones. We have developed an algorithm and experimented with it to evaluate and compare the three feature selection heuristics on ten data sets from UCI Repository. On average, simple correlation-based ensemble has the superiority in accuracy. The contex-tual merit-based heuristics seem to include too many features in the initial ensembles and iterations were most successful with it.