SVM Classifier 5-Fold Cross-Validation Performance Metrics

5-fold cross-validation performance of an SVM classifier, shared by author Sawera Qureshi on figshare. The dataset is a 5.5 KB Excel file last updated on May 21, 2026. Its specific contents likely include performance metrics like accuracy or precision from the validation process.

Use Cases

• Compare SVM classifier performance across different folds based on the cross-validation results.
• Benchmark SVM model stability based on the 5-fold validation metrics.
• Analyze variance in classifier performance using the provided cross-validation data.

Strengths

• Dataset is small (5.5 KB), ensuring quick download and easy inspection.
• Released under a permissive CC-BY-4.0 license, allowing for broad reuse and modification.
• Last update timestamp (2026-05-21 17:44:32) is provided for version tracking.

Limitations

• Row count is unknown, which may limit suitability assessment for statistical analysis.
• 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

Sawera Qureshi via figshare

Freshness

Last updated 2026-05-21 17:44:32; freshness should be verified.