| Issue |
E3S Web Conf.
Volume 500, 2024
The 1st International Conference on Environment, Green Technology, and Digital Society (INTERCONNECTS 2023)
|
|
|---|---|---|
| Article Number | 01015 | |
| Number of page(s) | 10 | |
| Section | Computer Science | |
| DOI | https://doi.org/10.1051/e3sconf/202450001015 | |
| Published online | 11 March 2024 | |
Investigating the Impact of Training and Testing Ratios on the Performance of an AI-Based Malware Detector using MATLAB
ECE Department, College of Engineering Our Lady of Fatima University, Quezon City, Philippines
* Corresponding author: cnromero@fatima.edu.ph
This research investigates the impact of the training and testing ratios on the performance of an AI-Based Malware Detector using MATLAB. The experiments through MATLAB have shown that higher training percentage means that a larger portion of dataset for training the model have been used while a lower training percentage shows that a large portion of the dataset reserved for testing the model’s performance. The exploration of the influence of training and testing ratios also have been able to determine the performance of an AI-Based Malware Detector. The results give to determining the relationship between training and testing ratios and the effectiveness of the malware detection system.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.