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Computer Science > Software Engineering

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By Thomas Bartz-Beielstein, Noah C. Pütz
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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[2409.16787] Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution

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By Thomas Bartz-Beielstein, Richard Schulz, Thomas Winter, Sebastian Spengler
| arxiv.org
[Submitted on 25 Sep 2024] Title:Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution View a PDF of the paper titled Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution, by Alexander Hinterleitner and 5 other authors View PDF HTML (experimental) Abstract:Research in Explainable Artificial Intelligence (XAI) is increasing, aiming to make deep learning models more transparent.
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[2406.00154] A Novel Ranking Scheme for the Performance Analysis of Stochastic Optimization Algorithms using the Principles of Severity

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By Thomas Bartz-Beielstein
| arxiv.org
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