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Ticket Priority Multiclass Log Loss Calculator
x402
Ticket Priority Multiclass Log Loss Calculator 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 multiclass log loss for a ticket priority classifier (low/normal/high) given up to 200 labelled records with predicted probabilities.
Price / call$0.01
Success—
StatusUnknown
How this service works
Ticket priority - Multiclass log loss: Multiclass log loss 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 multiclass log loss deliverable.
Output
Returns a bounded multiclass log loss deliverable — a scalar loss value computed across all supplied records with actual labels vs. predicted probability distributions for the three ticket priority classes (low, normal, high). Lower values indicate better-calibrated probability estimates.
Example use cases
Support ticket model evaluation
“I've got 120 support tickets with actual and predicted priorities (low, normal, or high) plus the probability arrays from my classifier — can you compute the multiclass log loss to see how well-calibrated it is?”
Naive-Bayes baseline benchmarking
“Run log loss evaluation on these 80 labelled tickets to benchmark my naive-Bayes ticket priority model before I move to a more complex approach — I have the actual labels, predicted labels, and probability scores for each.”
Regression test for retrained classifier
“My team just retrained our ticket triage model and I want to verify it hasn't gotten worse — here are 200 tickets with ground truth priorities and the new model's predicted probabilities, please compute the multiclass log loss.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-ticket-priority-log-loss?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, affordable ($0.01) evaluation of a ticket priority classifier's probability calibration using multiclass log loss on a small labelled dataset (up to 200 records). It is best suited for offline evaluation, regression testing after retraining, or benchmarking simple baselines — not for training models or handling large-scale datasets.
Side effects
- Fewer than 2 records supplied — minimum record count not met
- Probabilities array does not have exactly 3 elements per record
- Probabilities do not sum to approximately 1.0 — malformed distribution
- Invalid actual or predicted label outside enum [low, normal, high]
- Record ID exceeds 80-character limit or is empty
- More than 200 records supplied — exceeds maximum batch size
- Payment of 0.01 USDC not included or rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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