چکیده مقاله
One of the most persistent problems that are in the real world application is the class imbalance problem CIP When the class distributions are highly imbalanced data set are called imbalanced data set When the target class for traditional classifiers is smaller than other class, CIP occurs By CIP, the training data will significantly influence the classification accuracy Ensemble methods designed by researchers to avoid CIP Through analyzing the overall accuracy of ensemble methods, results suffer from over fitting problem This over fitting problem impressed other significant results of ensemble methods in classification of imbalanced data sets This paper analyzes and show how over fitting problem can suffer ensemble methods’ results in overall accuracy Consequently, verifies overcoming of over fitting problem in face of imbalanced data sets
کلیدواژهها
نویسندگان
Seyyedali Fattahi
Data Mining and Optimization Research Group, Centre for Artificial Intelligence, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, UKM Bangi, 43600, Selangor, Malaysia
Zalinda Othman
Data Mining and Optimization Research Group, Centre for Artificial Intelligence, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, UKM Bangi, 43600, Selangor, Malaysia
شیوه ارجاع
Fattahi, Seyyedali and Othman, Zalinda,1395,Handling imbalanced datasets:over fitting problem,3rd National Congress of Electrical and Computer Engineering of Iran,Tehran
ارائهشده در
مجموعه مقالات سومین کنفرانس سراسری نوآوری های اخیر در مهندسی برق و کامپیوتر19 شهریور 1395 · تهران