Real ML datasets¶
These examples use built-in scikit-learn datasets so the results are reproducible without downloads. They compare robustcov scores against familiar anomaly baselines.
Breast-cancer screening
Diagnostic tabular anomaly screening with baseline comparison.
Digits one-class anomaly
PCA image features with robust distances and anomaly baselines.
Wine class screening
Correlated chemical measurements with robust ensemble scores.
Multimodal anomaly detection
Cluster-aware robust distances for datasets with several valid modes.
How to use this topic¶
Start with the first card if you want the simplest demonstration. Then move to the more specialized page when the data shape matches your problem. Every page includes captured output, plots, interpretation notes, and a command to reproduce the result.