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Lead Stage Prediction Error Records
x402
Lead Stage Prediction Error Records is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Computes per-record prediction error metrics for a naive-Bayes lead stage classifier across four sales pipeline stages (enquiry, qualified, negotiation, closed).
Price / call$0.01
Success—
StatusUnknown
How this service works
Lead stage - Prediction error records: Prediction error records 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 prediction error records deliverable.
Output
A bounded set of prediction error records (up to 200 entries) detailing per-record classification errors for the lead stage classifier, including which records were mispredicted across the four stages (enquiry, qualified, negotiation, closed), derived from the supplied actual labels, predicted labels, and class probability arrays.
Example use cases
CRM model misclassification audit
“I've got 150 labelled CRM records where each one has an ID, the raw text, the true lead stage (enquiry, qualified, negotiation, or closed), what my model predicted, and the four probability scores — can you compute the prediction error records so I can see which leads are being misclassified and why?”
Sales pipeline classifier evaluation
“We're evaluating our naive-Bayes lead stage classifier and I need per-record error diagnostics for 80 test samples — each has an ID, text snippet, actual stage, predicted stage, and four class probabilities. Run the prediction error records analysis on them.”
Qualify vs negotiation confusion diagnosis
“My lead stage model keeps confusing 'qualified' and 'negotiation' records — I have 60 labelled examples with IDs, texts, actual stages, predicted stages, and probability arrays. Can you run the prediction error records calculation so I can pinpoint which records are contributing most to that confusion?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-lead-stage-errors?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, per-record prediction error diagnostics for a four-class lead stage text classifier without requiring a hosted model or foundation model training. It is ideal for small to medium local datasets (up to 200 records), quick evaluation loops, and debugging naive-Bayes baselines on CRM/sales pipeline data. Prefer alternatives if you need full model training, cross-validation over large corpora, or error analysis for classification problems outside the four lead stages.
Side effects
- More than 200 records submitted — request will be rejected or truncated
- Probability arrays with fewer or more than 4 values — schema validation error
- Invalid stage enum value in actual or predicted fields — rejected with validation error
- Malformed or missing required fields (id, text, actual, predicted, probabilities) — schema error
- Empty records array — returns empty or trivial error output
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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