Abstract

This paper develops the cascaded models for classification of PIMA Indian diabetes database. The k-nearest neighbour method is used to impute the missing data and the processed data is used for further classification. This is done in two steps, in first step k-means clustering algorithm is used for extracting hidden patterns in data set then in second step the classification is done by using suitable classifier. k-means algorithm combined with artificial neural network classifier and k-means algorithm combined with logistic regression classifier achieve classification accuracy above 98%.

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