A Hybrid Fuzzy Random Forest Algorithm Using Harmonic Search Algorithm for Parameter Tuning

In this paper, a hybrid fuzzy random forest algorithm, in which a harmony search algorithm is embedded for parameter tuning, is proposed for classification on unbalanced data sets. Firstly, the data set is fuzzified, and the fuzzy decision tree is constructed. Then, a harmony search algorithm is applied to adjust the category proportion, the hybrid fuzzy random forest algorithm is proposed. Finally, the effectiveness of the algorithm is verified using numerical examples with imbalanced datasets.