A Review on Diagnosis of Diabetes in Data Mining
Journal: International Journal of Science and Research (IJSR) (Vol.4, No. 6)Publication Date: 2015-06-05
Authors : Sukhjinder Singh; Kamaljit Kaur;
Page : 2406-2408
Keywords : Data Mining; Artificial neural fuzzy interference system; K-Nearest-Neighbor KNN; Machine Learning ML; Principal Component Analysis PCA;
Abstract
Data Mining is used for various purposes in many applications like industries, medical etc. This is used for extracting the useful information from the huge amount of data set. Health monitoring is also used the data mining concept for predict the diagnosis of the diseases. In health monitoring diabetes is the common health problem nowadays, which affects peoples. There are various data mining techniques and algorithm is used for finding the diabetes. Neural Network, Artificial neural fuzzy interference system, K-Nearest-Neighbor (KNN), Genetic Algorithm, Back Propagation algorithm etc. These techniques and the algorithms provide the better result to the people and the doctors regarding the diagnosis of the diabetes. From these results the people can predict he is affected with the diabetes or non-diabetes.
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