Artificial Neural Networks (ANNs) are a prominent machine learning technique that has lately been used in a variety of medical and medically related industries. Diabetes is a chronic condition that develops when blood sugar levels are too high. Early diagnosis of the condition may help to reduce consequences. The Artificial Neural Network is a well-known nonlinear data classifier. When building the network model, there are a few main aspects to consider. The input vectors' normalisation, learning rate parameter, and network structure. The proposed study examines several normalising approaches used in back propagation neural networks to improve the trained network's dependability. Based on the experimental results, the performance of the classifier model may be improved.
Author(S) Details
T. Jayalakshmi
LRG Government Arts College For Women, Tiruppur, India.
A. Santhakumaran
LRG Government Arts College For Women, Tiruppur, India.
View Book:- https://stm.bookpi.org/NRAMCS-V2/article/view/6790
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