Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid

This thesis presents the investigation on the performance of Artificial Neural Network (ANN) with Multilayer Perceptron (MLP) using Levenberg-Marquardt (LM) Algorithm in heart disease diagnosis. ANN aims to transform the inputs into the meaningful output. ANN is biological inspired and it has dynami...

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Main Author: Ab Hamid, Salbiah
Format: Thesis
Language:English
Published: 2010
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/69513/1/69513.pdf
https://ir.uitm.edu.my/id/eprint/69513/
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Institution: Universiti Teknologi Mara
Language: English
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spelling my.uitm.ir.695132023-03-27T07:58:48Z https://ir.uitm.edu.my/id/eprint/69513/ Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid Ab Hamid, Salbiah Neural networks (Computer science) Algorithms This thesis presents the investigation on the performance of Artificial Neural Network (ANN) with Multilayer Perceptron (MLP) using Levenberg-Marquardt (LM) Algorithm in heart disease diagnosis. ANN aims to transform the inputs into the meaningful output. ANN is biological inspired and it has dynamic characteristic which is learning. ANN is able to learn through experience and adaptation. It learns the types of input based on their weights and properties. MLP consist of interconnected input layer, hidden layer and output layer. The weight of each value in hidden layers will be considered during the learning process. LM algorithm is used to minimize the error during training and testing process. A transfer function simulation model is developed by using the MATLAB software. This ANN model is developed to facilitate heart disease diagnosis. 2010 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/69513/1/69513.pdf Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid. (2010) Degree thesis, thesis, Universiti Teknologi MARA (UiTM).
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Neural networks (Computer science)
Algorithms
spellingShingle Neural networks (Computer science)
Algorithms
Ab Hamid, Salbiah
Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid
description This thesis presents the investigation on the performance of Artificial Neural Network (ANN) with Multilayer Perceptron (MLP) using Levenberg-Marquardt (LM) Algorithm in heart disease diagnosis. ANN aims to transform the inputs into the meaningful output. ANN is biological inspired and it has dynamic characteristic which is learning. ANN is able to learn through experience and adaptation. It learns the types of input based on their weights and properties. MLP consist of interconnected input layer, hidden layer and output layer. The weight of each value in hidden layers will be considered during the learning process. LM algorithm is used to minimize the error during training and testing process. A transfer function simulation model is developed by using the MATLAB software. This ANN model is developed to facilitate heart disease diagnosis.
format Thesis
author Ab Hamid, Salbiah
author_facet Ab Hamid, Salbiah
author_sort Ab Hamid, Salbiah
title Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid
title_short Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid
title_full Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid
title_fullStr Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid
title_full_unstemmed Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid
title_sort evaluation of optimal mlp structure for heart disease diagnosis / salbiah ab hamid
publishDate 2010
url https://ir.uitm.edu.my/id/eprint/69513/1/69513.pdf
https://ir.uitm.edu.my/id/eprint/69513/
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