Comparison of aggregation classes in ensemble classifiers for high dimensional datasets

In the paper, we consider a combination of classifiers for the microarray datasets - examples of high dimensional datasets. Aggregation functions, in this case, are used to combine the output values of the constituent classifiers. Some known families of aggregation functions with several examples are studied and compared concerning their usefulness in the given classification method. Based on the proposed ranking of aggregations, the top aggregation functions considering their properties were explored to find which predispose to yield better classification results.