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- W2187570488 abstract "Search methods applied to data mining techniques help us to analyze a data set. These methods are used for reducing the size of the search space in order to select the relevant attribute for identification of diabetes .The research community in diabetes is very much depends on practical prediction and classification of diabetes parameters based on qualified dataset. The main intention in this context is to deal with a large data set with high accuracy. For this purpose models are built using weka tool under supervised learning algorithm. It is necessary to reduce the data dimension before constructing the models and thus the search methods for selection of attributes are followed. Those models are to be applied to predict the possible test cases for evaluation" @default.
- W2187570488 created "2016-06-24" @default.
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- W2187570488 date "2014-01-01" @default.
- W2187570488 modified "2023-09-27" @default.
- W2187570488 title "A NOVEL SUBSET SELECTION FOR CLASSIFICATION OF DIABETES DATASET BY ITERATIVE METHODS" @default.
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