Abstract
Thyroid disease is one of main origin of serious medical issues for human subsistence. Therefore, proper diagnosis of thyroid disease is treated as an important issue to determine treatment for patients. A new approach on Multi-layer Perception (MLP) using back propagation learning algorithm to classify Thyroid disease is presented. It consists of an input layer with 4 neurons, 10 hidden layer with 3 neurons and an output layer with just 1 neuron. The relevant choice of activation objective and the number of neurons in the hidden layer and also the number of layers are achieved using MLP test and error method. The proposed method shows better performance in terms of classification accuracy. For simulation results MATLAB Tool is used.
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Nageshwar Rao, B., Laxmi Srinivasa Reddy, D., Bhaskar, G. (2020). Thyroid Diagnosis Using Multilayer Perceptron. In: Satapathy, S.C., Raju, K.S., Shyamala, K., Krishna, D.R., Favorskaya, M.N. (eds) Advances in Decision Sciences, Image Processing, Security and Computer Vision. ICETE 2019. Learning and Analytics in Intelligent Systems, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-030-24322-7_56
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DOI: https://doi.org/10.1007/978-3-030-24322-7_56
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