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DEVELOPING AN INTEGRATED ARTIFICIAL INTELLIGENCE MODEL BASED ON DATAMINING IN THE EARLY DETECTION, DIAGNOSIS AND PREDICTION OF DIABETES

Shubham Bhardwaj

Vol. 1, Jan-Jun 2016

Abstract:

The process of selecting, categorizing, and evaluating transformations are all components called database knowledge discovery model, used to extract useful models and information from data. The two main types of machine learning algorithms are supervised and unsupervised. Unsupervised algorithms can draw interferences from data sets, whereas supervised learning algorithms use the experience to predict new or invisible data. Directed learning is likewise depicted as order. This study employs classification methods to produce a more precise classification. The classification algorithm has been applied to the Indian Diabetes Dataset of the PIMA of the Public Foundation of Diabetes, Stomach-related and Kidney Sicknesses which contains information on diabetic ladies

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