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Feedback Theme Multiclass Log Loss Calculator
x402
Feedback Theme 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 2026-10-19).
Computes multiclass log loss over up to 200 labelled feedback-theme text records using local naive-Bayes evaluation tools.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feedback theme - Multiclass log loss: Multiclass log loss for Feedback theme. 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 value computed over the submitted labelled text records, reflecting how well predicted class probabilities align with actual feedback theme labels across quality, price, delivery, and support categories.
Example use cases
Evaluating feedback classifier calibration
“I trained a naive-Bayes model to classify customer feedback into quality, price, delivery, and support. Can you calculate the multiclass log loss across my 120 labelled test records, with the actual label, predicted label, and four class probabilities for each one?”
Comparing two feedback models by log loss
“I have two feedback classifiers and want to pick the better one. Can you compute the multiclass log loss for my 80 labelled records using the first model's predicted probabilities across quality, price, delivery, and support classes?”
Monitoring production model drift
“Our feedback theme model has been running for a month and I want to check if performance has degraded. Can you run multiclass log loss on these 200 recent labelled records with actual vs predicted labels and probability scores for the four categories?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-feedback-theme-log-loss?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, inexpensive multiclass log loss evaluation specifically for feedback theme classification (quality, price, delivery, support) with up to 200 pre-labelled records and pre-computed class probabilities. It is ideal when you have your own model's outputs and want a standardised metric without needing a hosted model or foundation-model training.
Side effects
- More than 200 records submitted — exceeds batch limit
- Probabilities array does not contain exactly 4 values per record
- Probability values outside [0,1] range
- Invalid or missing actual/predicted label not in allowed enum
- Empty records array returns no result
- Malformed record IDs or missing required fields cause validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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