ds@mcpanalytics.aiEmail your data and your question and get an answer about your own data, with the method shown.Email your data and question. Get an answer.
Upload your data and get a complete classification threshold optimizer report. Free.
The practical guide behind this tool: when it applies, how to read the output, and the traps that make it say the wrong thing.
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.
Interactive scatter visualization
Interactive table visualization
Interactive table visualization
Interactive table visualization
Plain-English reading of the results and what to do next.
Pick the churn-flag cutoff that minimises the real cost of a missed churner versus a wasted retention offer
See our FAQ for pricing, privacy and how the analysis works.
MCP Analytics. Classification Threshold Optimizer. Free tool. https://mcpanalytics.ai/free/standard_threshold_optimizer. Accessed [date you used it].
Your turn
Bring your own data and the question you actually need answered.
MCP AnalyticsData science by email Send us your data and your question, and we will reply. ds@mcpanalytics.ai
Tell us what went wrong, in your own words. We capture the page you're on automatically, so no need to describe where you are.