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Knowledge Topic Top-k Label Coverage
x402
Knowledge Topic 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 2026-10-16).
Computes top-k label coverage metrics for a knowledge topic classifier given up to 200 labelled text records with predicted probabilities.
Price / call$0.01
Success—
StatusUnknown
How this service works
Knowledge topic - Top-k label coverage: Top-k label coverage for Knowledge topic. 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 top-k label coverage metric indicating the proportion of supplied records where the true label appears among the top k predicted labels ranked by probability, computed locally over the submitted dataset of up to 200 records across four knowledge topic categories: setup, usage, troubleshooting, and reference.
Example use cases
Classifier coverage check before deployment
“Before I ship my knowledge base topic classifier, can you run a top-2 label coverage check on these 20 labeled records — each has an actual category (setup, usage, troubleshooting, or reference), a predicted label, and 4 probability scores — and tell me how often the true label lands in the top 2 predictions?”
Comparing k values for support doc routing
“I'm tuning a support document router that classifies articles into setup, usage, troubleshooting, and reference. Can you compute the top-k label coverage for k=1, k=2, and k=3 separately on my 50 labeled samples with their probability arrays so I can see how much coverage improves as k increases?”
Spot-checking a naive-Bayes baseline model
“I trained a simple naive-Bayes model to categorize knowledge articles into setup, usage, troubleshooting, and reference, and I have 30 test records with predicted labels and probability outputs. Can you calculate the top-3 label coverage to see if my baseline is good enough before investing in a bigger model?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-knowledge-topic-top-k?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a lightweight, local top-k label coverage evaluation for a four-class knowledge topic classifier (setup, usage, troubleshooting, reference) without sending data to a hosted model or foundation model. Ideal for fast, low-cost ($0.01) spot-checks on small datasets up to 200 records using your own predicted labels and probability scores.
Side effects
- More than 200 records submitted — endpoint only accepts up to 200 labelled records
- Probability array length not exactly 4 — each record requires exactly 4 probability values
- k value outside range 1–4 — will be rejected
- Invalid label values — actual and predicted must be one of: setup, usage, troubleshooting, reference
- Malformed record missing required fields (id, text, actual, predicted, probabilities) — validation error
- Payment of 0.01 USDC not completed via x402 protocol — request rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| k | integer | |
| records | array |
Tags
x402
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