Title :
The Effect of Imbalanced Data Class Distribution on Fuzzy Classifiers - Experimental Study
Author :
Visa, Sofia ; Ralescu, Anca
Author_Institution :
Dept. of Electr. Comput. & Eng. Comput. Sci., Cincinnati Univ., OH
Abstract :
This study evaluates the robustness of a fuzzy classifier when class distribution of the training set varies. The analysis of the results is based on the classification accuracy and ROC curves. The experimental results reported here show that fuzzy classifiers are less variant with the class distribution and less sensitive to the imbalance factor than decision trees
Keywords :
fuzzy set theory; learning (artificial intelligence); pattern classification; statistical analysis; ROC curve; data class distribution; decision tree; fuzzy classifier; imbalance factor; training set; Classification tree analysis; Costs; Decision trees; Error correction; Fuzzy sets; Machine learning algorithms; Minimization methods; Robustness; Testing; Training data;
Conference_Titel :
Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on
Conference_Location :
Reno, NV
Print_ISBN :
0-7803-9159-4
DOI :
10.1109/FUZZY.2005.1452488
