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Sentiment Grouped Dataset Split
x402
Sentiment 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 up to 200 labelled sentiment text records into grouped train/test subsets for local evaluation and naive-Bayes baseline comparison.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sentiment - Grouped dataset split: Grouped dataset split for Sentiment. 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 grouped dataset split deliverable partitioning up to 200 supplied labelled text records by sentiment class (positive, neutral, negative) into train/test groups, suitable for local evaluation and naive-Bayes baseline benchmarking. No hosted model or foundation-model training is included.
Example use cases
E-commerce review dataset prep
“I have 120 product reviews already labelled positive, neutral, or negative — split them into grouped train and test sets so I can run a local naive-Bayes sentiment baseline evaluation.”
Social media sentiment evaluation
“Here are 180 social media posts I labelled for sentiment — positive, neutral, and negative — can you do a grouped dataset split so I can see how well my labels hold up across partitions?”
Support ticket sentiment benchmarking
“I've got 90 support tickets manually tagged with sentiment labels. Run a grouped split on them by sentiment class so I can evaluate coverage and build a local baseline model.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-sentiment-dataset-split?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a small labelled sentiment corpus (up to 200 records) and need a fast, inexpensive grouped train/test split with naive-Bayes baseline evaluation — particularly for local dataset work without access to a hosted model or foundation-model training pipeline. Ideal for quick sanity-checking of labelled sentiment data or benchmarking annotation quality.
Side effects
- Fewer than 2 records supplied — minimum input not met
- More than 200 records supplied — maxItems exceeded
- Missing required fields (id, text, actual) on any record
- Invalid 'actual' enum value (must be positive, neutral, or negative)
- Record ID exceeds 80 characters or text exceeds 1000 characters
- Insufficient class diversity to produce meaningful grouped split
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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