• K.Gandhimathi

Diabetes is one of the disease increases in humanity across the world-wide. Data mining is a process of extracting the information from a large dataset and transforms it into understandable structure. Medical data mining has been a great capability for finding hidden patterns from the large data sets of the medical dataset. The Data mining techniques used for the prediction of diseases like heart diseases, cancer, kidney stones, EEG etc. Prediction of Diabetes is an emerging and fastest growing technology in the medical analysis data. This research paper concentrates on the clustering method for grouping diabetic data based on cluster head attributes. In this paper the popular clustering algorithm Fuzzy C-Means (FCM) is selected and analyzed based on their fundamentals by using diabetes dataset. The algorithm performance is tested based on its execution time range values. The values are displayed in chart to predict best algorithm.

Fuzzy C-Means (FCM), Clustering, and Diabetes dataset

"PREDICTION OF TYPE 2 DIABETIC USING FUZZY C-MEANS CLUSTERING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 2, page no.a287-a291, February-2023, Available :http://www.jetir.org/papers/JETIR2302040.pdf

"PREDICTION OF TYPE 2 DIABETIC USING FUZZY C-MEANS CLUSTERING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 2, page no. ppa287-a291, February-2023, Available at : http://www.jetir.org/papers/JETIR2302040.pdf