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Feedback Theme Label Distribution
x402
Feedback Theme Label Distribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Computes the label distribution (class balance) across up to 200 labelled feedback text records categorized by quality, price, delivery, or support themes.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feedback theme - Label distribution: Label distribution for Feedback theme. 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 label distribution deliverable.
Output
Returns a label distribution report showing the count and/or proportion of records assigned to each feedback theme (quality, price, delivery, support) across the submitted dataset of up to 200 labelled records.
Example use cases
Pre-training class imbalance check
“Before I train my feedback classifier, can you analyze the label distribution across my 150 labelled records tagged as quality, price, delivery, or support so I can see if any category is underrepresented?”
QA audit of annotation batch
“I just finished labelling a batch of 80 customer reviews as quality, price, delivery, or support — can you give me a breakdown of how many records fall into each category so I can spot any annotation bias?”
Feedback dataset evaluation report
“I have a set of 120 customer feedback samples with labels for quality, price, delivery, and support — can you compute the label distribution so I know the percentage split across those four themes?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-feedback-theme-label-balance?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, lightweight check of label balance across customer feedback records categorized into quality, price, delivery, or support themes — especially useful before training a naive-Bayes or similar classifier, or when auditing annotation batches for class imbalance. It is ideal for small local datasets up to 200 records and does not require a hosted model or external training infrastructure.
Side effects
- Fewer than 2 records submitted — minimum input not met
- More than 200 records submitted — exceeds maximum allowed batch size
- Invalid label value used (only quality, price, delivery, support are allowed)
- Missing required fields (id, text, or actual) on any record
- Empty text field or id exceeding 80 characters — schema validation error
- Payment not included or insufficient — x402 payment required at $0.01 USDC
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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