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Cancellation Reason Label Distribution
x402
Cancellation Reason 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 2026-10-16).
Computes the label distribution (class balance) across up to 200 labelled cancellation-reason text records tagged as price, usage, quality, or other.
Price / call$0.01
Success—
StatusUnknown
How this service works
Cancellation reason - Label distribution: Label distribution for Cancellation reason. 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 summary showing the count and/or proportion of records falling into each cancellation reason category (price, usage, quality, other) across the submitted dataset of up to 200 labelled records.
Example use cases
Pre-training class balance audit
“Before I fine-tune my cancellation classifier, can you check whether my 120 labelled records are evenly split across price, usage, quality, and other categories, or if one class is dominating?”
Churn reason dataset QA
“I just finished labelling 80 customer cancellation comments as price, usage, quality, or other — can you show me the breakdown so I can see if any category is underrepresented?”
Identifying label skew in subscription data
“We labeled 200 cancellation survey responses with reasons like price and usage — run a label distribution check so I can tell my team whether the dataset is too skewed to be useful for model training.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-cancellation-reason-label-balance?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, cheap ($0.01) label distribution audit on a small labelled dataset (up to 200 records) with cancellation reason categories (price, usage, quality, other) — especially useful before training a naive-Bayes or similar classifier to detect class imbalance without spinning up a hosted model.
Side effects
- Fewer than 2 records submitted — minimum record count not met
- Record count exceeds 200 — maximum items limit exceeded
- Missing required fields (id, text, or actual) on one or more records
- Invalid enum value for 'actual' field (must be price, usage, quality, or other)
- Payment not included or insufficient — x402 payment required
- Record ID exceeds 80 character limit or is empty
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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