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Project Status Prediction Error Records
x402
Project Status 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 2026-10-20).
Accepts up to 200 labelled text records with actual and predicted project status classifications and returns prediction error analysis using naive-Bayes evaluation tools.
Price / call$0.01
Success—
StatusUnknown
How this service works
Project status - Prediction error records: Prediction error records for Project status. 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 deliverable containing up to 200 prediction error records — identifying which labelled text records were misclassified by the project status model, including record IDs, texts, actual vs. predicted labels, and probability scores for erroneous predictions.
Example use cases
Audit sprint classifier mistakes
“I ran my naive-Bayes project status classifier on 50 tickets and I want to know exactly which ones it got wrong — here are the records with their text, actual status (planned, active, blocked, complete), predicted status, and the four class probabilities for each. Can you run the prediction error analysis and show me the misclassified ones?”
Validate model before production deploy
“Before I ship my project status model, I need to verify its error records on a test set of 120 labelled documents — each has an ID, the text, the true label (planned/active/blocked/complete), the model's predicted label, and four probability scores. Can you compute the prediction error records so I can review failures?”
Debug active vs blocked confusion
“My classifier keeps mixing up 'active' and 'blocked' project statuses. I have 30 records where it might be going wrong — with the text, actual and predicted labels, and probabilities. Can you pull the prediction error records so I can see exactly which ones it misclassified?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-project-status-errors?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local naive-Bayes-based prediction error analysis for project status text classification (planned, active, blocked, complete) on small datasets up to 200 records, without requiring a hosted model or foundation model training. Ideal for fast, low-cost ($0.01) error auditing and classifier debugging.
Side effects
- More than 200 records submitted — batch size limit exceeded
- Probabilities array does not contain exactly 4 elements — schema validation error
- Invalid label values outside enum (planned, active, blocked, complete) — rejected
- Missing required fields (id, text, actual, predicted, probabilities) — validation failure
- Empty records array — no data to evaluate
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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