Machine Learning Model Performance Comparison with Accuracy and AUC-ROC Metrics

Comparative performance of machine learning models showing accuracy and AUC-ROC values. The dataset was authored by Muhammad Ishaq and last updated on March 17, 2026. It is a 5.5 KB Excel file available under a CC-BY-4.0 license on figshare.

Use Cases

• Benchmarking machine learning models based on reported accuracy and AUC-ROC values.
• Analyzing trade-offs between different model types using the comparative performance metrics.
• Selecting a model for a predictive task based on the provided performance comparison.
• Educational demonstration of model evaluation metrics like accuracy and AUC-ROC.

Strengths

• Small file size (5.5 KB) enables quick download and inspection.
• Explicitly licensed for reuse under CC-BY-4.0.
• Focuses on two standard model evaluation metrics: accuracy and AUC-ROC.

Limitations

• Row count and specific column definitions are unknown, limiting suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Muhammad Ishaq via figshare.

Collection Method

Likely compiled from model evaluation experiments.

Time Range

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Freshness

Last updated 2026-03-17 17:36:51; freshness should be verified.

Geography

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