Heterogeneous versus Homogeneous Machine Learning Ensembles
نویسندگان
چکیده
منابع مشابه
Pooling homogeneous ensembles to build heterogeneous ensembles
In ensemble methods, the outputs of a collection of diverse classifiers are combined in the expectation that the global prediction be more accurate than the individual ones. Heterogeneous ensembles consist of predictors of different types, which are likely to have different biases. If these biases are complementary, the combination of their decisions is beneficial. In this work, a family of het...
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ژورنال
عنوان ژورنال: Information Technology and Management Science
سال: 2015
ISSN: 2255-9094
DOI: 10.1515/itms-2015-0021