D. Rengasamy

Feature importance in machine learning models: A fuzzy information fusion approach

Mercedes Torres Torres, M. Alexander, G. Figueredo, 2022, Neurocomputing.

Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems using Feature Importance Fusion pdf

Divish Rengasamy, Benjamin Rothwell, Grazziela Figueredo, 2020, Applied Sciences.

Deep Learning with Dynamically Weighted Loss Function for Sensor-Based Prognostics and Health Management

Divish Rengasamy, Benjamin Rothwell, Xin Chen, 2020, Sensors.

Load prediction using support vector regression

Yee Wan Wong, Rajprasad Kumar Rajkumar, Divish Rengasamy, 2017, TENCON 2017 - 2017 IEEE Region 10 Conference.

Mechanistic Interpretation of Machine Learning Inference: A Fuzzy Feature Importance Fusion Approach pdf

Grazziela P. Figueredo, Divish Rengasamy, Benjamin Rothwell, 2021, ArXiv.

EFI: A Toolbox for Feature Importance Fusion and Interpretation in Python

Mercedes Torres Torres, G. Figueredo, Aayush Kumar, 2022, LOD.

Deep Learning Approaches to Aircraft Maintenance, Repair and Overhaul: A Review

Grazziela Patrocinio Figueredo, Divish Rengasamy, Hervé P. Morvan, 2018, 2018 21st International Conference on Intelligent Transportation Systems (ITSC).

Machine learning to determine the main factors affecting creep rates in laser powder bed fusion

Grazziela P. Figueredo, Divish Rengasamy, Benjamin Rothwell, 2021, J. Intell. Manuf..