[HTML][HTML] Type 2 diabetes data classification using stacked autoencoders in deep neural networks
K Kannadasan, DR Edla, V Kuppili - Clinical Epidemiology and Global …, 2019 - Elsevier
Objective This paper aims to classify the Pima Indians diabetes dataset with better accuracy
and other evaluation metrics. The Deep Neural Network (DNN) framework will help to
diagnose the patient in an effective way with higher accuracy. Method In this approach, we
proposed a Deep Neural Network framework for diabetes data classification using stacked
autoencoders. Features are extracted from the dataset using stacked autoencoders and the
dataset is classified using softmax layer. Also, fine tuning of the network is done using …
and other evaluation metrics. The Deep Neural Network (DNN) framework will help to
diagnose the patient in an effective way with higher accuracy. Method In this approach, we
proposed a Deep Neural Network framework for diabetes data classification using stacked
autoencoders. Features are extracted from the dataset using stacked autoencoders and the
dataset is classified using softmax layer. Also, fine tuning of the network is done using …
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