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Classification Threshold Optimizer In Minutes

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What's in the report?

Standard-library analysis: where should the cutoff go on your model score, given what YOUR errors actually cost? Map the true yes/no outcome and a predicted probability or score, and every candidate cutoff is swept — precision, recall, F1, specificity, accuracy and expected cost at each. The report gives the optimum under several named criteria (maximum F1, Youden's J, minimum expected cost from your own cost of a false positive and a false negative, and the cutoff that meets a target precision or recall), the metric-versus-threshold curves as the headline chart, and — for every cutoff — the cost ratio it implicitly assumes. If no costs are supplied, the criteria are shown side by side rather than one being picked for you.

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Metric Curves by Cutoff

Interactive scatter visualization

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Criteria Side by Side

Interactive table visualization

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Confusion Matrix at the Chosen Cutoff

Interactive table visualization

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In-Sample Optimism, Stability & Balance

Interactive table visualization

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AI Insights

Plain-English interpretation — what the numbers mean, what's significant, and what to do next.

The Question This Answers

Pick the churn-flag cutoff that minimises the real cost of a missed churner versus a wasted retention offer

Questions?

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.

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