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Review Aspect Classification — Supplied-Group Evaluation
x402
Review Aspect Classification — Supplied-Group Evaluation 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).
Evaluates a supplied set of labeled text records (up to 200) for review aspect classification accuracy, broken down by user-defined group, using local naive-Bayes baselines and dataset tools.
Price / call$0.01
Success—
StatusUnknown
How this service works
Review aspect - Supplied-group evaluation: Supplied-group evaluation for Review aspect. 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 supplied-group evaluation deliverable.
Output
Returns a group-level evaluation report covering classification metrics (such as accuracy, per-class breakdowns, and confusion data) for each supplied group, along with naive-Bayes baseline comparisons, for up to 200 labeled records across the four aspect categories: performance, appearance, value, and other.
Example use cases
Per-segment classifier audit for product reviews
“I've got 150 labeled product review records tagged as performance, appearance, value, or other — each record also has an actual label and my model's predicted label, and they're split into two retailer groups. Can you run a group evaluation so I can see which retailer segment my classifier is weakest on?”
Naive-Bayes baseline comparison for aspect model
“I want to compare my review aspect model's predictions against a naive-Bayes baseline. I have 80 records with actual and predicted aspect labels grouped by region. Can you evaluate them and show me group-level accuracy?”
QA check on aspect labeling across annotator groups
“We have 200 text records that two annotator groups labeled with aspect categories — performance, appearance, value, or other — and a model also made predictions. Can you evaluate how well each annotator group aligns with the model predictions using a group breakdown?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-review-aspect-group-evaluation?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a lightweight, low-cost group-level evaluation of a text classifier for review aspect categories (performance, appearance, value, other) on a small labeled dataset (up to 200 records), especially when you want per-group metrics and a naive-Bayes baseline without standing up a hosted model or using a foundation model.
Side effects
- More than 200 records supplied — request rejected or truncated
- Missing required fields (id, text, actual, predicted, group) on any record — validation error
- Invalid enum value for actual or predicted (must be performance, appearance, value, other) — schema error
- Empty records array — no evaluation possible
- Payment not included or insufficient USDC — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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