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Meeting Topic Classifier — Macro, Micro & Weighted Scores
x402
Meeting Topic Classifier — Macro, Micro & Weighted Scores 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 macro, micro, and weighted precision/recall/F1 evaluation scores for a meeting-topic text classifier across planning, progress, decision, and review categories.
Price / call$0.01
Success—
StatusUnknown
How this service works
Meeting topic - Macro micro and weighted scores: Macro micro and weighted scores 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 macro micro and weighted scores deliverable.
Output
Returns macro-averaged, micro-averaged, and weighted-averaged precision, recall, and F1 scores computed across all supplied labelled records for the four meeting topic classes (planning, progress, decision, review), along with supporting metrics derived from the confusion of actual vs. predicted labels.
Example use cases
Evaluate sprint meeting classifier
“I built a model that tags sprint meeting notes as planning, progress, decision, or review. I have 80 labelled examples with both actual and predicted labels — can you compute the macro, micro, and weighted scores so I can see how it's performing?”
Compare two model runs on meeting data
“I have 120 meeting text records where I've recorded the ground-truth topic labels and the predictions from my updated classifier. Run the aggregate scoring — macro, micro, and weighted — so I can see if the new version improved over the baseline.”
Validate naive Bayes meeting topic model
“I trained a simple naive Bayes model to classify meeting notes into planning, progress, decision, and review. I have 60 test records with actual and predicted labels — can you give me the macro, micro, and weighted precision, recall, and F1 to validate it?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-meeting-topic-aggregate-scores?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, cheap ($0.01), self-contained evaluation of a meeting-topic text classifier using standard multi-class metrics (macro, micro, weighted) without setting up your own sklearn pipeline. Ideal for lightweight CI checks on model quality, ad-hoc benchmarking of up to 200 labelled examples, or comparing classifier iterations across planning/progress/decision/review categories. Not suitable if you need per-class breakdown tables, confusion matrices, or evaluation on more than 200 records at once.
Side effects
- More than 200 records supplied — endpoint caps at 200 records per call
- Missing required fields (id, text, actual, or predicted) on any record causes validation failure
- Labels outside the allowed enum values (planning, progress, decision, review) are rejected
- Empty records array returns no meaningful scores
- Text exceeding 1000 characters per record may be truncated or rejected
- Payment of 0.01 USDC not completed — x402 payment required before response is returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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