confidence.
Evidence Lab
Laboratory principles. Practical ML evaluation.
A browser-based workbench that trains a logistic regression classifier on synthetic assay quality-control data, then separates threshold selection from held-out testing.
- Reproducible data generation and training-only preprocessing
- Sensitivity, specificity, ROC AUC and confidence intervals
- Calibration, error review and locked acceptance criteria
- External model-score CSV evaluation and report export



