چکیده مقاله
Throughout the Data explosion era, dimension reduction is a vital area of machine learning techniques to achieve useful and reduced data sets On the other side, ensemble models have consensus mechanism to take advantage of positive point of several clustering techniques concurrently between the various clustering algorithms that suffer from negative aspects In this study, we use an ensemble clustering model with k means to aim dimension reduction, two co association matrix, two consensus functions to aggregate clustering results, also PCA The model significantly reduces data sets dimensions by feature extraction techniques We applied NMI performance validity index to evaluate results The simulation results show this model acquires better clustering performance for all data sets while accomplish feature extraction
کلیدواژهها
نویسندگان
Zeinab Hassani
Computer Sciences Department, Basic sciences Department, University of Kosar, Bojnord, Iran
Elham Enayati
Computer Sciences Department, Basic sciences Department, University of Bojnord, Bojnord, Iran
شیوه ارجاع
Hassani, Zeinab and Enayati, Elham,1399,An Ensemble Clustering Model for Dimension Reduction,4th National Conference on Computer, Information Technology and Applications of Artificial Intelligence,Ahvaz
ارائهشده در
مجموعه مقالات چهارمین کنفرانس ملی کامپیوتر، فناوری اطلاعات و کاربردهای هوش مصنوعی15 بهمن 1399 · اهواز