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Identifying the Diagnosis of Diabetes Mellitus by using AK-Mode Algorithm




Data Mining, Diabetic Approach, Clustering, AK-Mode Algorithm, Performance Evaluation


Data mining aims at withdrawal of previously anonymous information from large databases. It can be observed as an automated solicitation of algorithms to discover hidden patterns and to extract information from data. Medicine is a new route in his undertaking is to prevent, diagnose and medicate diseases using data mining. Generally the data mining techniques, gathering and decision tree induction were used. Clustering is used to group patients according to the overall presence/absence of obliterations at the tested markers. Decision trees remained used to examine the resulting clustering and look for associations between deletion patterns, populations and the experimental of infertility. Decision support system to deliver Analytical Processing techniques are used to provide analysis of data. However, in order to integrate data mining results with data has to be demonstrated in a particular type of schema. The proposed work aims at the comparison of four algorithms called AK-mode algorithm, K-mode Algorithm, ROCK Algorithm, And MULIC Algorithm. Finally AK-mode Algorithm provides better results compared with the other algorithms.

Other Details

Paper ID: IJSRDV4I70149
Published in: Volume : 4, Issue : 7
Publication Date: 01/10/2016
Page(s): 101-104

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