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Support Intent Grouped Dataset Split
x402
Support Intent 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 2026-10-12).
Splits a labelled support-intent dataset (billing/technical/account/other) into grouped train/test partitions and returns dataset split deliverables with naive-Bayes baseline evaluation metrics.
Price / call$0.01
Success—
StatusUnknown
How this service works
Support intent - Grouped dataset split: Grouped dataset split for Support intent. 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 containing partitioned train and test subsets of the supplied labelled records, stratified by support intent category (billing, technical, account, other), along with naive-Bayes baseline evaluation metrics computed locally on the split.
Example use cases
Baseline evaluation for support chatbot
“I have 80 labelled customer support messages tagged as billing, technical, account, or other — can you do a grouped dataset split and run a naive-Bayes baseline so I can see how well these categories separate?”
Train/test split for intent classifier
“Take these 150 labelled support intent records and split them into grouped train and test partitions — I need the split deliverable before I start building my classifier.”
Audit support label quality with split
“I've got 60 support tickets manually labelled across billing, technical, account, and other — run a grouped dataset split on them so I can check whether the label distribution looks reasonable across splits.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-support-intent-dataset-split?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 pre-labelled support intent text records (billing, technical, account, other) and need a grouped train/test split with a local naive-Bayes baseline — no hosted model or foundation-model API required, no external ML infrastructure, and the $0.01 per-call cost makes it ideal for quick, lightweight dataset evaluation and split preparation.
Side effects
- Fewer than 2 records supplied — minimum record count not met
- More than 200 records supplied — maxItems limit exceeded
- Record missing required fields (id, text, actual) — schema validation error
- Invalid 'actual' enum value not in [billing, technical, account, other] — rejected record
- Insufficient records per category to form meaningful grouped split — may return degenerate split
- Payment failure via x402 — endpoint returns 402 and no deliverable is produced
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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