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Lead Stage Confidence Calibration Bins
x402
Lead Stage Confidence Calibration Bins is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Computes confidence calibration bins for a multi-class lead stage classifier (enquiry, qualified, negotiation, closed) from up to 200 labelled records with predicted probabilities.
Price / call$0.01
Success—
StatusUnknown
How this service works
Lead stage - Confidence calibration bins: Confidence calibration bins for Lead stage. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded confidence calibration bins deliverable.
Output
Returns binned confidence calibration statistics for the supplied lead stage records, including accuracy and average confidence per bin across the four classes (enquiry, qualified, negotiation, closed), enabling reliability diagram construction and ECE/calibration error assessment.
Example use cases
CRM model calibration audit
“I have 120 labelled leads from our CRM with actual stages (enquiry, qualified, negotiation, closed), the model's predicted stages, and the four class probability scores for each. Can you compute confidence calibration bins so I can see where the model is overconfident or underconfident?”
Sales pipeline classifier QA
“Before we ship this lead scoring model to production, can you run calibration bin analysis on these 80 validation records? Each record has the true lead stage, predicted stage, and a 4-element probability array summing to 1.”
Comparing two model versions
“I want to compare calibration quality between our old and new lead stage models. Here are 150 records with actual labels, predicted labels, and predicted probabilities for the new model — compute the calibration bins so I can benchmark it.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-lead-stage-calibration?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a trained multi-class lead stage classifier producing probability outputs and need to evaluate how well-calibrated those probabilities are across the four pipeline stages, without requiring a hosted model or cloud training infrastructure. Ideal for lightweight, local-style calibration analysis at very low cost ($0.01 per call) on datasets up to 200 records.
Side effects
- Records array empty or missing — validation error returned
- Probabilities array does not have exactly 4 elements per record — schema rejection
- Probability values outside [0,1] range — validation failure
- More than 200 records supplied — request rejected or truncated
- Actual or predicted labels outside allowed enum values — schema error
- Malformed JSON body — HTTP 400 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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