Model Evaluation Results from Five-Fold Cross-Validation

Model evaluation results across five-fold cross-validation. The dataset is a 5.5 KB XLS file authored by Ruping Zhang and last updated on June 1, 2026. It is shared under a CC-BY-4.0 license on the figshare platform.

Use Cases

• Compare model performance metrics across different folds based on the cross-validation results.
• Analyze the variance in model evaluation scores based on the five-fold methodology.
• Benchmark new models against the reported evaluation results.
• Validate the stability of a machine learning model's performance.

Strengths

• File size is precisely 5.5 KB, indicating a small, focused dataset.
• Has a clear, permissive license (CC-BY-4.0).
• Includes a specific last updated timestamp (2026-06-01 17:52:55).

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 generated from a machine learning model evaluation process.

Freshness

Last updated 2026-06-01 17:52:55; freshness should be verified.