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Meeting Topic Classifier – Top-k Label Coverage
x402
Meeting Topic Classifier – 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 metrics for a naive-Bayes meeting topic classifier across up to 200 labelled text records with 4 categories: planning, progress, decision, review.
Price / call$0.01
Success—
StatusUnknown
How this service works
Meeting topic - Top-k label coverage: Top-k label coverage for Meeting 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 score indicating the proportion of records where the true label appears among the top-k highest-probability predicted classes, computed over the supplied batch of up to 200 meeting topic records.
Example use cases
Validate meeting classifier before deployment
“Before I ship my meeting topic model, can you compute the top-2 label coverage across these 50 labelled meeting transcripts? Each record has the actual topic (planning, progress, decision, or review), the model's top prediction, and its 4 class probability scores.”
Compare k=1 vs k=2 coverage for model selection
“I'm choosing between two meeting classifiers and want to see their top-1 label coverage using these 80 test records with actual labels and predicted probabilities across planning, progress, decision, and review — set k to 1.”
Audit naive-Bayes baseline on small meeting dataset
“Can you compute top-3 label coverage for a naive-Bayes meeting topic baseline I trained? I have 30 labelled records with actual and predicted categories and all 4 class probabilities — the classes are planning, progress, decision, and review.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-meeting-topic-top-k?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, cheap ($0.01 USDC) evaluation metric for a 4-class meeting topic classifier and already have model predictions and probabilities in hand. It is ideal for small local datasets (up to 200 records) where you want to measure top-k coverage without training or calling a hosted model. Prefer it over full retraining pipelines or foundation-model APIs when the goal is purely metric computation on pre-classified records.
Side effects
- More than 200 records submitted — batch size limit exceeded
- Probabilities array length not exactly 4 for each record
- k value outside allowed range of 1–4
- Label values outside the allowed enum (planning, progress, decision, review)
- Malformed record missing required fields (id, text, actual, predicted, probabilities)
- Probabilities not summing to approximately 1.0 per record
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| k | integer | |
| records | array |
Tags
x402
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