Airfoil Self-Noise Data for Predictive Model Evaluation

The airfoil_self_noise dataset was curated by the TabArena team in 2014 for a study on independent and identically distributed tabular data. It originates from NASA research by Brooks, Pope, and Marcolini published in 1989. The intended task for this dataset is regression.

Use Cases

• Evaluating regression model performance on IID tabular data based on the dataset's stated focus.
• Predicting aerodynamic noise levels based on features related to airfoil geometry and flow conditions.
• Benchmarking machine learning algorithms for tasks in acoustics and fluid dynamics.

Strengths

• Dataset has a clear, stated purpose for evaluating predictive models on IID tabular regression tasks.
• Original data source is a cited NASA technical report, providing authoritative provenance.
• License is CC BY 4.0, permitting open sharing and adaptation.

Limitations

• Row count, column names, and sample data are unknown, which limits suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

NASA research by Brooks, Thomas F., D. Stuart Pope, and Michael A. Marcolini (1989).

Collection Method

Curated from the original source by the TabArena team.

Time Range

Original research published in 1989; dataset curated in 2014.

Freshness

Dataset Year is 2014; last updated date is unknown.

Geography

Likely reflects data from aerodynamic experiments, but specific geography is unknown.