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Subscription Request Fixed-Holdout Learning Curve
x402
Subscription Request Fixed-Holdout Learning Curve 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).
Generates a fixed-holdout learning curve for subscription request text classification (upgrade/downgrade/cancel/renew) using a naive-Bayes baseline on up to 200 labelled records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Subscription request - Fixed-holdout learning curve: Fixed-holdout learning curve for Subscription request. 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 fixed-holdout learning curve deliverable.
Output
Returns a fixed-holdout learning curve deliverable showing classifier accuracy (naive-Bayes baseline) at incrementally larger training set sizes, evaluated against a fixed holdout split, for the four subscription intent classes (upgrade, downgrade, cancel, renew).
Example use cases
SaaS churn signal training assessment
“I've collected 150 customer messages labelled as cancel, renew, upgrade, or downgrade and want to know how quickly a naive-Bayes model learns from them — can you run a fixed-holdout learning curve on these records so I see accuracy at different training sizes?”
Labelling budget decision for subscription NLP
“We're deciding how many subscription request texts to label for our classifier — can you compute a fixed-holdout learning curve on the 80 labelled examples I have so far, tagged as upgrade, downgrade, cancel, or renew, so I can see if more labels are worth the cost?”
Baseline benchmark before fine-tuning LLM
“Before we invest in fine-tuning a large model, I want a naive-Bayes learning curve baseline on our 200 subscription intent records (upgrade, downgrade, cancel, renew) — run the fixed-holdout evaluation and tell me what accuracy we're getting at various training set sizes.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-subscription-request-learning-curve?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 labelled subscription request texts (upgrade/downgrade/cancel/renew) and need a fast, cheap fixed-holdout learning curve using a naive-Bayes baseline — ideal for deciding how much labelled data to collect before investing in larger models, with no need for hosted or foundation model training.
Side effects
- Fewer than 2 records provided — minimum input not met
- Records missing required fields (id, text, actual) — validation error
- More than 200 records submitted — exceeds maximum input limit
- Invalid class label in 'actual' field (must be upgrade/downgrade/cancel/renew) — schema rejection
- Highly imbalanced classes with very few records may produce unreliable curve estimates
- Payment of 0.01 USDC not completed — request rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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