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Cascaded Modeling for PIMA Indian Diabetes Data
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 139 - Number 11 |
| Year of Publication: 2016 |
| Authors: M.S. Barale, D.T. Shirke |
10.5120/ijca2016909426
|
M.S. Barale, D.T. Shirke . Cascaded Modeling for PIMA Indian Diabetes Data. International Journal of Computer Applications. 139, 11 ( April 2016), 1-4. DOI=10.5120/ijca2016909426
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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