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Ticket Priority Grouped Dataset Split
x402
Ticket Priority 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 2026-10-18).
Splits a labelled ticket-priority dataset (up to 200 records) into grouped train/test partitions for local ML evaluation and naive-Bayes baseline benchmarking.
Price / call$0.01
Success—
StatusUnknown
How this service works
Ticket priority - Grouped dataset split: Grouped dataset split for Ticket priority. 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
A bounded grouped dataset split deliverable: the supplied labelled ticket records (up to 200, each with id, text, and actual priority label of low/normal/high) partitioned into grouped train and test sets, suitable for local ML evaluation and naive-Bayes baseline benchmarking. No hosted model or foundation-model training is included.
Example use cases
Support team ML baseline evaluation
“I have 150 support tickets already labelled as low, normal, or high priority. Can you split them into a grouped dataset partition so I can run a naive-Bayes baseline and see how well the labels hold up?”
Ticket triage model benchmarking
“Here are 80 customer support tickets tagged by priority — split them into grouped train and test sets so I can benchmark a ticket triage classifier locally.”
Balanced class split for priority classifier
“I need a grouped dataset split for my ticket priority data — I've got about 60 records spread across low, normal, and high priority labels. Can you partition them so each priority class is represented in the split?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-ticket-priority-dataset-split?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a small labelled dataset (up to 200 records) of support tickets tagged with low/normal/high priority and need a quick grouped train/test split for local evaluation or naive-Bayes baseline benchmarking — without requiring a hosted model or foundation-model fine-tuning pipeline. Best suited for lightweight, local ML workflows at minimal cost.
Side effects
- Fewer than 2 records supplied — minimum input not met
- More than 200 records supplied — exceeds maxItems limit
- Missing required fields (id, text, or actual) on any record
- Invalid priority label value (must be 'low', 'normal', or 'high')
- Record text exceeds 1000 character limit
- Record ID exceeds 80 character limit or is empty
- Payment of 0.01 USDC not completed via x402 protocol
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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