Document Type
White Paper
Publication Date
2024
DOI
10.25776/g0ay-c833
Pages
1-7
Abstract
This research introduces a benchmark framework, called EDUMX, designed for machine learning (ML)- based forecasting and XAI tasks, leveraging the Streamlit open-source Python library. The framework offers a comprehensive suite of functionalities, including data loading, feature selection, relationship analysis, data preprocessing, model selection, metric evaluation, training, and real-time monitoring. Users can easily upload data in diverse formats, explore relationships between variables, preprocess data using various techniques, and assess the performance of the ML model using customizable metrics. With its user-friendly interface, this framework offers invaluable insights for forecasting tasks in various domains, catering to the evolving needs of predictive analytics. EDUMX is available for all to use. Please contact mkuzlu@odu.edu if you would like the details to access this tool.
Rights
Included with kind permission from the authors.
Original Publication Citation
Kuzlu, M., Ozdemir, G., Ozdemir, U. (2024). A benchmark framework for data visualization and explainable AI (XAI) [White paper]. ODU Global, Old Dominion University. https://online.odu.edu/media/white-paper-benchmark-framework-data-visualization-and-explainable-ai-xai
ORCID
0000-0002-8719-2353 (Kuzlu), 0000-0002-3175-6893 (Ozdemir, G.)
Repository Citation
Kuzlu, Murat; Ozdemir, Gokcen; and Ozdemir, Umut, "A Benchmark Framework for Data Visualization and Explainable AI (XAI)" (2024). Engineering Technology Faculty Publications. 240.
https://digitalcommons.odu.edu/engtech_fac_pubs/240