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Ticket Priority Prediction Error Records
x402
Ticket Priority 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 2026-10-12).
Computes and returns prediction error records for a naive-Bayes ticket priority classifier given up to 200 labelled text records with actual and predicted labels plus class probabilities.
Price / call$0.01
Success—
StatusUnknown
How this service works
Ticket priority - Prediction error records: Prediction error records for Ticket priority. 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
Returns up to 200 prediction error records for the supplied ticket priority classification data, detailing per-record outcomes including misclassification flags and associated metadata derived from actual labels, predicted labels, and class probabilities for low, normal, and high priority classes.
Example use cases
Auditing support ticket triage model
“I've got 120 support tickets where my model predicted low, normal, or high priority — each one has the actual label and the three class probabilities. Can you send these through the ticket priority prediction error records tool so I can see which ones were misclassified?”
Comparing naive-Bayes baseline accuracy
“I want to evaluate my naive-Bayes ticket priority classifier. I have 80 labelled records with actual and predicted labels plus probabilities for each class. Can you run the prediction error records analysis and tell me where the errors are?”
Diagnosing high-priority ticket misses
“My ticket classifier keeps missing high-priority issues — I have 200 labelled examples with actual vs predicted priority and the probability scores. Can you compute the prediction error records so I can identify the patterns in where it fails?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-ticket-priority-errors?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need per-record prediction error diagnostics for a ticket priority (low/normal/high) text classifier, especially when working with small labelled datasets up to 200 records and a naive-Bayes baseline. It is best suited for offline evaluation and auditing of classifier outputs rather than real-time inference or training large models.
Side effects
- Fewer than 2 records supplied returns a validation error
- More than 200 records supplied exceeds the maxItems limit and is rejected
- Probabilities array missing exactly 3 values causes schema validation failure
- Probability values outside 0–1 range are rejected
- Invalid enum values for actual or predicted fields (not low/normal/high) cause errors
- Missing required fields (id, text, actual, predicted, probabilities) result in bad request errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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