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Running roc curve & classifier cutoff analysis...
Sent to — interactive charts, statistical results, R code, and AI insights.
Analyze another fileStandard-library analysis: evaluate a binary classifier or diagnostic score against the true yes/no outcome. Draws the full ROC curve, computes the AUC with a 95% confidence interval, and finds the best operating cutoff by Youden's J — with sensitivity, specificity, PPV, NPV, accuracy, and the confusion counts at that cutoff. Works on any dataset: map the true outcome and a numeric score where higher means more likely positive.
Interactive scatter visualization
Interactive table visualization
Interactive table visualization
Plain-English interpretation — what the numbers mean, what's significant, and what to do next.
Judge whether a churn or fraud score is good enough to act on
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
Run any analysis on your own data — validated R analyses, interactive reports, AI insights, and PDF export.
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