Adam optimization algorithm for wide and deep neural network

The objective of this research is to evaluate the effects of Adam when used together with a wide and deep neural network. The dataset used was a diagnostic breast cancer dataset taken from UCI Machine Learning. Then, the dataset was fed into a conventional neural network for a benchmark...

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Bibliographic Details
Main Authors: Mohd Jais, Imran Khan, Ismail, Amelia Ritahani, Syed, Qamrun Nisa
Format: Article
Language:English
Published: 2019
Subjects:
Online Access:http://irep.iium.edu.my/77293/1/77293_Adam%20optimization%20algorithm%20for%20wide.pdf
http://irep.iium.edu.my/77293/
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
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Summary:The objective of this research is to evaluate the effects of Adam when used together with a wide and deep neural network. The dataset used was a diagnostic breast cancer dataset taken from UCI Machine Learning. Then, the dataset was fed into a conventional neural network for a benchmark test. Afterwards, the dataset was fed into the wide and deep neural network with and without Adam. It was found that there were improvements in the result of the wide and deep network with Adam. In conclusion, Adam is able to improve the performance of a wide and deep neural network.