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- W3126281330 abstract "Now a day's diabetes is becoming a major health issue in the world for men and women. To extract meaningful data from medical datasets or databases we can use techniques of data mining and machine learning models. In this article, for classifying the data properly machine learning model called multilayer perceptron (MLP) with optimal stochastic gradient descent (SGD) proposed. Radial basis function (RBF) model as an outlier detection method is used for removing the misclassified instances then removed instances passed to the multilayer perceptron with a stochastic gradient descent classifier model for classifying the data more effectively. Performance of MLP-SGD is good to compare to other classifiers but the usage of RBF took the performance of the proposed model to the higher level compared to existing models." @default.
- W3126281330 created "2021-02-15" @default.
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- W3126281330 date "2020-10-01" @default.
- W3126281330 modified "2023-10-14" @default.
- W3126281330 title "Predicting Diabetes Using Outlier Detection and Multilayer Perceptron with Optimal Stochastic Gradient Descent" @default.
- W3126281330 cites W1989022033 @default.
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- W3126281330 doi "https://doi.org/10.1109/indiscon50162.2020.00023" @default.
- W3126281330 hasPublicationYear "2020" @default.
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