Performance of Model Selection and Validation for Cross-Cohort Experiments

A dataset containing performance metrics for model selection and validation in cross-cohort experiments. The data is stored in an XLS file of 9.5 KB, authored by Matthew Herbert Ning and last updated on April 30, 2026. It is licensed under CC-BY-4.0 and hosted on figshare.

Use Cases

• Comparing model selection methods based on reported performance metrics.
• Analyzing model validation results across different experimental cohorts.
• Evaluating the performance of linear discriminant analysis with Oracle Approximating Shrinkage (LDA OA).
• Assessing the confidence intervals for model performance in cross-cohort studies.

Strengths

• Includes 95% confidence intervals for performance metrics, providing statistical context.
• Explicitly defines the LDA OA method used in the analysis.
• File size of 9.5 KB indicates a focused, manageable dataset for targeted analysis.

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 contains results from computational experiments on model selection and validation.

Time Range

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Freshness

Last updated 2026-04-30 17:31:49; freshness should be verified.

Geography

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