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Meeting Topic Grouped Dataset Split
x402
Meeting Topic Grouped Dataset Split 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).
Splits a labelled meeting-topic dataset into grouped train/test partitions using naive-Bayes baseline tooling for the four meeting topic classes.
Price / call$0.01
Success—
StatusUnknown
How this service works
Meeting topic - Grouped dataset split: Grouped dataset split 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 grouped dataset split deliverable.
Output
Returns a bounded grouped dataset split deliverable: the input records partitioned into train and test groups by meeting topic label (planning, progress, decision, review), along with a naive-Bayes baseline evaluation on the split — no hosted model or foundation-model training involved.
Example use cases
Baseline model evaluation for meeting classifier
“I have 80 annotated meeting transcript snippets labelled as planning, progress, decision, or review. Can you run a grouped dataset split on them and give me the naive-Bayes baseline results so I can see how well a simple model would do?”
Preparing meeting data for a new ML pipeline
“Before I hand my meeting-topic dataset off to the ML team, I need a clean grouped train/test split. I've got 120 records each tagged with one of these labels: planning, progress, decision, or review — can you produce that split?”
Validating label balance across meeting categories
“I want to check whether my 60 labelled meeting records are well-distributed across planning, progress, decision, and review before training. Can you do a grouped dataset split so I can see how the categories fall out in the partitions?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-meeting-topic-dataset-split?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 labelled meeting-topic text records and need a quick, reproducible grouped train/test split with a naive-Bayes baseline — ideal for lightweight local evaluation before committing to a larger model training pipeline. It is purpose-built for the four-class meeting topic schema (planning, progress, decision, review) and costs only $0.01 per call, making it suitable for iterative dataset assessment.
Side effects
- Fewer than 2 records supplied — minItems validation error
- More than 200 records supplied — maxItems validation error
- Record text exceeds 1000 characters — field-level validation error
- Invalid label value outside enum (planning/progress/decision/review) — schema rejection
- Insufficient class representation for grouped split — degenerate split or error returned
- Missing required fields (id, text, actual) — schema validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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