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Review Aspect Grouped Dataset Split
x402
Review Aspect 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 review-aspect text records into a grouped train/test dataset split with local evaluation and naive-Bayes baselines.
Price / call$0.01
Success—
StatusUnknown
How this service works
Review aspect - Grouped dataset split: Grouped dataset split for Review aspect. 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 containing train and test partitions of the supplied labelled review-aspect records (up to 200), along with local evaluation metrics and a naive-Bayes baseline performance report. No hosted model is trained; results are local and bounded to the supplied data.
Example use cases
E-commerce review classifier preparation
“I have 120 product reviews each labelled as performance, appearance, value, or other — can you split them into grouped train and test sets and run a naive-Bayes baseline so I know how separable these categories are?”
Small-scale aspect model benchmarking
“Here are 80 customer review snippets I've manually tagged by aspect. Split them into a grouped dataset partition and give me a local evaluation with a baseline classifier to see if my labels are consistent.”
Review aspect label quality audit
“I want to check the quality of my review aspect annotations — I have 200 records tagged as performance, appearance, value, or other. Can you do a grouped dataset split and run the naive-Bayes evaluation to flag any problematic label distributions?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-review-aspect-dataset-split?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a small labelled dataset (up to 200 records) of product review text already tagged by aspect (performance, appearance, value, other) and need a quick grouped train/test split with a local naive-Bayes baseline evaluation — without standing up a hosted model or using a foundation model. Ideal for label quality checks, feasibility assessments, and lightweight ML experiments at minimal cost ($0.01 per call).
Side effects
- Fewer than 2 records supplied — minimum input not met
- More than 200 records supplied — exceeds maximum item limit
- Invalid aspect label used outside enum (performance/appearance/value/other)
- Record text exceeds 1000 character limit — truncation or rejection
- ID field missing or empty — required field validation failure
- Unbalanced class distribution may degrade naive-Bayes baseline metrics
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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