Machine Learning Performance Metrics With and Without Data Augmentation

Muthulakshmi Kirubakaran published a dataset comparing key metrics for machine learning models trained with and without data augmentation under an identical training budget. The dataset is stored as a 5.5 KB Excel file on figshare and was last updated on May 18, 2026. It is distributed under the CC-BY-4.0 license.

Use Cases

• Compare model performance metrics between augmented and non-augmented training regimes.
• Benchmark the efficiency of data augmentation strategies under a fixed computational budget.
• Validate the effectiveness of augmentation techniques for specific machine learning tasks implied by the metrics.

Strengths

• Dataset provides a direct comparison under controlled conditions with an identical training budget.
• The 5.5 KB file size suggests a focused and concise set of results.
• It is published under the permissive CC-BY-4.0 license.

Limitations

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

Provenance

Source

Muthulakshmi Kirubakaran via figshare

Freshness

Last updated 2026-05-18 17:47:18; freshness should be verified.