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modelcardr 0.4.0

• Added unified auditing for binary classification, multiclass classification, and regression.
• Added automatic task detection with explicit overrides for numeric class codes.
• Added multiclass confusion matrices, class-level precision/recall/F1, macro and weighted metrics, one-vs-rest AUC, multiclass log loss and Brier score, and top-label calibration.
• Added regression MAE, RMSE, MSE, R-squared, bias, MAPE, SMAPE, normalized errors, residual diagnostics, and subgroup error analysis.
• Extended pass/fail requirements and plain-language risk warnings to all supported tasks.
• Updated HTML, Markdown, JSON, and plotting behavior to be task-specific.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.