Study of Ensemble Learning Algorithm with Stacking Framework

Nowadays the most active research in supervised learning includes an integration of several base classifiers into the combined classification system. Such systems are known under the names multiple classifiers, ensembles methods. An ensemble of classifiers is a set of classifiers whose decisions are to classify new examples. Slacked generalization or stacking is a ensemble learning method for constructing classifier ensembles. Stacking is an ensemble that uses different “type� of base classifiers. An ensemble of classifiers is first created, whose outputs are used as inputs to a second level meta-classifier. In the area of bioinformatics, classification is widely used. The datasets of bioinformatics are very too much large and complex. So F-score and entropy based technique is used for reducing dataset. The proposed system will achieve reliable accuracies when has been tested on bioinformatics dataset.