Climate-Specific Machine Learning Model Performance Metrics

Usman Ali published a dataset on figshare in 2026 containing machine learning model performance metrics. The data likely includes R² scores and demographic consequence assessments from a 5-fold cross-validation procedure. The dataset is 5.5 KB in size and is available in XLS format.

Use Cases

• Benchmarking climate model performance based on reported R² scores.
• Assessing demographic disparities in model outcomes using the independent samples t-test results.
• Comparing model stability across different climate conditions based on the standard deviation of performance metrics.

Strengths

• Performance metrics are reported as mean ± standard deviation, providing a measure of central tendency and variability.
• Model evaluation uses a 5-fold cross-validation method, which is a standard technique for robust performance estimation.
• The dataset is openly available under a CC-BY-4.0 license, permitting reuse with attribution.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Collection Method

Likely derived from a machine learning model evaluation study.

Freshness

Last updated 2026-04-30 17:54:59; freshness should be verified.