TY  - JOUR
TI  - Comparison of FCM, PCM, FPCM and PFCM Algorithms in Clustering Methods
AB  - Clustering is a process of dividing the objects into subgroups so that the same set of data is similar, butthe data of different clusters is different. The basis of the fuzzy clustering algorithms is the C- Meansfamilies and the strongest algorithm is the Fuzzy C-means (FCM) algorithm. In this study; FCM,Possibilistic Fuzzy C-means (PFCM), Fuzzy Possibilistic C-means (FPCM) and Possibilistic C- means (PCM)algorithms are used to classify the several real data sets which are E.coli, wine and seed data sets intodifferent clusters by MATLAB program. Also, the results of PFCM, FPCM, PCM and FCM algorithms arecompared according to the classification accuracy, root mean squared error (RMSE) and mean absoluteerror (MAE). The results show that the PFCM and FPCM algorithms have better performance than FCMand PCM according to criteria for comparing the performances.
AU  - KAYA, ASLI AYTEN
AU  - ÖZDEMİR, ÖZER
DO  - 10.35414/akufemubid.429540
PY  - 2019
JO  - Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi
VL  - 19
IS  - 1
SN  - 2149-3367
SP  - 92
EP  - 102
DB  - TRDizin
UR  - http://search/yayin/detay/312067
ER  -