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Release Change Multiclass Brier Score
x402
Release Change Multiclass Brier Score is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Computes the multiclass Brier score for a release-change classifier (feature/fix/documentation/maintenance) given up to 200 labelled text records with predicted probabilities.
Price / call$0.01
Success—
StatusUnknown
How this service works
Release change - Multiclass Brier score: Multiclass Brier score for Release change. 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 brier score deliverable.
Output
Returns the multiclass Brier score — a single bounded numeric metric quantifying the mean squared error between predicted class probabilities and one-hot encoded actual labels across all submitted records and classes. Lower scores indicate better probabilistic predictions.
Example use cases
Evaluate release classifier probability calibration
“I've got 120 changelog entries labelled as feature, fix, documentation, or maintenance, and my classifier output probability vectors for each — can you compute the multiclass Brier score so I can see how well-calibrated the predictions are?”
Compare two models on release type prediction
“I'm comparing two release-change classifiers. Can you compute the Brier score for model A's predictions? I'll give you 80 records with the actual labels and the four-class probability outputs so we can see which model is better calibrated.”
Benchmark baseline model before retraining
“Before I retrain my release categorization model, I want a baseline Brier score on 150 sample records with actual labels (feature, fix, documentation, maintenance) and the current model's predicted probabilities — can you calculate that for me?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-release-change-brier?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a lightweight, pay-per-call multiclass Brier score calculation specifically for release-change classification (feature/fix/documentation/maintenance) without needing to set up your own evaluation infrastructure. Ideal for quick benchmarking of local models or naive-Bayes baselines on small datasets up to 200 records. Prefer over general-purpose ML platforms when cost and simplicity matter and the label set matches exactly.
Side effects
- Records array is empty or missing — returns validation error
- Probabilities array does not contain exactly 4 values per record — returns schema error
- Probability values outside [0,1] range — rejected by schema validation
- Actual or predicted label not in allowed enum (feature, fix, documentation, maintenance) — schema rejection
- More than 200 records submitted — exceeds maximum batch limit
- Payment of 0.01 USDC not completed — 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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