Effect of Hyper-Parameter Optimization on the Deep Learning Model Proposed for Distributed Attack Detection in Internet of Things Environment
Machine Learning
2018-06-20 v1 Cryptography and Security
Machine Learning
Abstract
This paper studies the effect of various hyper-parameters and their selection for the best performance of the deep learning model proposed in [1] for distributed attack detection in the Internet of Things (IoT). The findings show that there are three hyper-parameters that have more influence on the best performance achieved by the model. As a consequence, this study shows that the model's accuracy as reported in the paper is not achievable, based on the best selections of parameters, which is also supported by another recent publication [2].
Cite
@article{arxiv.1806.07057,
title = {Effect of Hyper-Parameter Optimization on the Deep Learning Model Proposed for Distributed Attack Detection in Internet of Things Environment},
author = {Md Mohaimenuzzaman and Zahraa Said Abdallah and Joarder Kamruzzaman and Bala Srinivasan},
journal= {arXiv preprint arXiv:1806.07057},
year = {2018}
}
Comments
6 pages, 2 figures and 2 tables