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Lead Stage Fixed-Holdout Learning Curve
x402
Lead Stage 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 2026-10-15).
Generates a fixed-holdout learning curve for a naive-Bayes text classifier across four lead pipeline stages (enquiry, qualified, negotiation, closed) using up to 200 labelled records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Lead stage - Fixed-holdout learning curve: Fixed-holdout learning curve for Lead stage. 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
A fixed-holdout learning curve report showing how naive-Bayes text classification accuracy and related metrics change as training set size increases, evaluated against a held-out portion of the supplied labelled records across the four lead stages (enquiry, qualified, negotiation, closed).
Example use cases
Sales pipeline classifier data sufficiency check
“I have 150 labelled lead notes tagged as enquiry, qualified, negotiation, or closed — can you run a fixed-holdout learning curve to tell me if I have enough data for a reliable naive-Bayes classifier?”
Early-stage lead scoring model benchmark
“We're just starting to build a lead scoring model and have 40 text samples across the four pipeline stages. Run a learning curve so I can see how accuracy trends as we add more labelled examples.”
Comparing classifier performance across lead stages
“I want to know which of my lead stages — enquiry, qualified, negotiation, or closed — the classifier struggles with most as training data grows. I have 180 labelled records, can you generate the fixed-holdout learning curve?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-lead-stage-learning-curve?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 labelled lead-stage text records and want a lightweight, local naive-Bayes baseline learning curve without deploying or fine-tuning a hosted model. It is ideal for quick feasibility checks on data sufficiency for CRM lead classification pipelines at minimal cost ($0.01 USDC).
Side effects
- Fewer than 2 records supplied returns a validation error
- Records missing required fields (id, text, actual) are rejected
- Invalid 'actual' label values outside the enum cause schema errors
- Exceeding 200 records triggers a max-items validation error
- Insufficient class representation may produce degenerate learning curves
- Text fields exceeding 1000 characters per record are truncated or rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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