A . 5 Heterogeneous Ensemble Classifiers
نویسندگان
چکیده
Recent results in solving classification problems indicate that the use of ensembles classifier models often leads to improved performance over using single classifier models [1, 2, 3, 4]. In this talk, we discuss heterogeneous ensemble classifier models, where the member classifier models are not of the same model type. A discussion of the issues associated with creating such classifiers along with a brief description of the new HEterogeneous Machine Learning Open Classification Kit (HEMLOCK) will be presented. Results for a problem of text classification and several standard multi-class test problems illustrate the performance of heterogeneous ensemble classifiers.
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