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Review Aspect Top-k Label Coverage
x402
Review Aspect Top-k Label Coverage 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 top-k label coverage metric for a review aspect classifier given up to 200 labelled records with predicted probabilities.
Price / call$0.01
Success—
StatusUnknown
How this service works
Review aspect - Top-k label coverage: Top-k label coverage 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 top-k label coverage deliverable.
Output
Returns a bounded top-k label coverage metric indicating what fraction of records have the correct label appearing within the top-k ranked predictions, computed from the supplied probability arrays and actual labels.
Example use cases
Evaluating product review aspect classifier
“I've trained a classifier to categorize product reviews into performance, appearance, value, or other. Can you calculate the top-2 label coverage across my 80 test records to see how often the correct label lands in the top 2 predictions?”
Comparing k=1 vs k=3 coverage on review data
“Run a top-3 label coverage calculation on my 120 review aspect records — each record has actual labels and predicted probabilities for performance, appearance, value, and other — I want to see how coverage improves going from k=1 to k=3.”
QA check on aspect model before deployment
“Before I ship this review aspect model, can you run a top-k label coverage evaluation at k=2 on my 200 held-out test records with their predicted probabilities to confirm the coverage meets our threshold?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-review-aspect-top-k?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a lightweight, local top-k label coverage evaluation for a 4-class review aspect classification task (performance, appearance, value, other) without requiring a hosted model or foundation-model training pipeline. Best suited for small-batch evaluation (up to 200 records) at minimal cost ($0.01 USDC) when you already have predicted probabilities and ground-truth labels and just need the coverage metric computed.
Side effects
- More than 200 records submitted — request rejected or truncated
- Probability arrays not summing correctly or containing values outside [0,1]
- k value outside allowed range (1–4) causing validation error
- Mismatched label enums (values outside performance/appearance/value/other) causing schema rejection
- Malformed record structure missing required fields triggering 4xx error
- Empty records array returning undefined or zero metric
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| k | integer | |
| records | array |
Tags
x402
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