Reading Recommendation: “Beyond algorithm hyperparameters: on preprocessing hyperparameters and associated pitfalls in machine learning applications”

The preprint, which was written by Christina Sauer, Anne-Laure Boulesteix, Luzia Hanßum, Farina Hodiamont, Claudia Bausewein, and Theresa Ullmann, is available on arXiv: https://arxiv.org/abs/2412.03491 Abstract: … More

Reading Recommendation: “SCORE Band Visualizations: Supporting Decision Makers in Comparing High-Dimensional Outcome Vectors in Multiobjective Optimization”

The paper contributes to visualizing such outcome vectors independent of how they have been generated.

New arXiv Preprint: Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution

The article explores the integration of Explainable Artificial Intelligence (XAI) in enhancing deep learning performance. Focusing on regression problems, it introduces a feature selection pipeline using Integrated Gradients and k-means clustering, applied to blade vibration analysis in turbo machinery development.