Random Forest Classifier Performance with 5-Fold Cross-Validation

5.5 KB of performance data for a Random Forest classifier evaluated using 5-fold cross-validation. The dataset was authored by Sawera Qureshi and is available under a CC-BY-4.0 license. It was last updated on 2026-05-21.

Use Cases

• Benchmarking Random Forest classifier performance based on cross-validation results.
• Analyzing model stability and variance based on 5-fold cross-validation splits.
• Comparing classification algorithms using reported performance metrics.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Specific evaluation method (5-fold cross-validation) is clearly stated.
• License (CC-BY-4.0) is permissive for reuse.

Limitations

• Row count and specific performance metrics are unknown, limiting 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 contains results from a machine learning experiment.

Freshness

Last updated 2026-05-21 17:44:34; freshness should be verified.