TOP 文献データベース Effect of Hyper-Parameter Optimization on the Deep Learning Model Proposed for Distributed Attack Detection in Internet of Things Environment
arxiv
Effect of Hyper-Parameter Optimization on the Deep Learning Model Proposed for Distributed Attack Detection in Internet of Things Environment
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].