Decoding Mobile App Performance with Explainable AI (XAI)

Dimensions

Archana, D and Deepthi Sri, R and Deva Dharani, P and Haripriya, S and Vimala Varshini, C P (2024) Decoding Mobile App Performance with Explainable AI (XAI). In: 2024 International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC), Coimbatore, India.

Full text not available from this repository.

Official URL: https://doi.org/10.1109/ICSSEECC61126.2024.1064940...

Abstract

The document discusses the development of a mobile application software for small, wireless computing devices, emphasizing the importance of a clear strategy for app success. It introduces Interpretable AI to elucidate prediction results on mobile app success factors and assist developers. An Ensemble Machine Learning Algorithm is used, along with Explainable AI models like LIME and SHAP, achieving a prediction accuracy of 96%.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Black boxes; Ensemble machine learning; Explainable artificial intelligence; Machine learning algorithms; Machine-learning; Mobile app; Mobile application software; Performance; Success factors; Wireless computing devices
Subjects:	A Artificial Intelligence and Data Science > Machine Learning A Artificial Intelligence and Data Science > Artificial intelligence C Computer Science and Engineering > Mobile Computing C Computer Science and Engineering > Wireless Network
Divisions:	Electronics and Communication Engineering
Depositing User:	Dr Krishnamurthy V
Date Deposited:	21 Sep 2024 08:42
Last Modified:	21 Sep 2024 08:42
URI:	https://ir.psgitech.ac.in/id/eprint/1144

Actions (login required)

: View Item