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Meeting Topic Local Text Classifier (Naive-Bayes)
x402
Meeting Topic Local Text Classifier (Naive-Bayes) is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Trains a local naive-Bayes text classifier on up to 200 labelled meeting-transcript records and classifies new query texts into planning, progress, decision, or review categories.
Price / call$0.01
Success—
StatusUnknown
How this service works
Meeting topic - Train local text baseline and classify: Train local text baseline and classify 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 train local text baseline and classify deliverable.
Output
Returns per-query predicted meeting topic labels (planning, progress, decision, or review) derived from a locally-trained naive-Bayes text baseline fitted on the supplied labelled records, along with evaluation metadata about the trained model.
Example use cases
Auto-tag meeting agenda items
“I have 80 labelled examples of meeting agenda text already tagged as planning, progress, decision, or review — train a classifier on them and then classify these 5 new agenda snippets so I know how to route them.”
Evaluate meeting transcript classifier
“I want to see how well a simple naive-Bayes model does on our internal meeting notes — here are 120 labelled records across planning, progress, decision, and review; train the baseline and classify these 10 holdout texts.”
Categorize customer success meeting notes
“We have weekly customer success meetings and I want to automatically sort the notes into planning, progress, decision, and review buckets — I've got 60 labelled examples ready, can you train a local classifier and predict categories for these new entries?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-meeting-topic-local-classifier?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, cheap, interpretable text classification baseline for meeting topics using only your own labelled data — no hosted model, no foundation model API calls, no data leaving your control beyond this single bounded call. Ideal for prototyping, evaluation, or low-volume use cases where a naive-Bayes local classifier is sufficient and cost ($0.01 USDC) matters. Prefer alternatives if you need deep-learning accuracy, large-scale inference, or topic discovery on unlabelled data.
Side effects
- Fewer than 2 records supplied (minItems violation)
- More than 200 records supplied (maxItems exceeded)
- Missing required fields (id, text, actual) on any record
- Invalid actual label value outside enum (planning/progress/decision/review)
- Text exceeds 1000-character limit per record
- No query_texts provided or query_texts exceeds 20 items
- Insufficient class diversity for a meaningful classifier (e.g. only one class represented)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array | |
| query_texts | array |
Tags
x402
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