Performance Evaluation of Autism Diagnosis Tool at Diverse Learning Rates

Authors

  • Vikas Khullar IKG Punjab Technical University and CT Institute of Engineering Management and Technology
  • Manju Bala

Abstract

Abstract: Artificial Neural Networks (ANN) has been considered as a major artifact in the scenario of Machine Learning, which needs optimization for more accurate and efficient results. The main aim of this paper is to identify the optimization techniques and their learning rates for ANN with better results. In this paper, we have been utilized “Keras” library for framing ANN with different optimization techniques. The evaluation of the optimization techniques has conducted on the basis of accuracy and loss as parameters. On the basis of our comparative study, we have proposed the best ANN optimization technique out of our evaluated techniques for the diagnosis of available Autism Spectrum Disorder (ASD) dataset.

Keywords – Artificial Neural Network, Optimization, Autism Spectrum Disorder.

Cite this Article

Vikas Khullar, Manju Bala, Harjit Pal Singh. Performance Evaluation of Autism Diagnosis Tool at Diverse Learning Rates. Journal of Artificial Intelligence Research & Advances. 2019; 6(2): 92–99p.

Downloads

Published

2019-07-19

Issue

Vol. 6 No. 2 (2019)

Section

Research Articles

License

Declaration and Copyright Transfer Form

(to be completed by authors)

I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.

  • I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.
  • I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).
  • I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.
  •  I/We also agree to the authorship of the article in the following order:

Author’s name                                    

 

1. ________________

2. ________________

3. ________________

4. ________________

 

We  Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal.