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Lead Stage Grouped Three-Fold Baseline Evaluation
x402
Lead Stage Grouped Three-Fold Baseline Evaluation 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).
Runs a grouped three-fold cross-validation using a naive-Bayes classifier on up to 200 labelled lead-stage text records across four CRM stages (enquiry, qualified, negotiation, closed).
Price / call$0.01
Success—
StatusUnknown
How this service works
Lead stage - Grouped three-fold baseline evaluation: Grouped three-fold baseline evaluation 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 grouped three-fold baseline evaluation deliverable.
Output
Returns a grouped three-fold cross-validation result including per-fold and aggregate accuracy metrics from a naive-Bayes baseline classifier applied to the supplied labelled text records across the four lead stages (enquiry, qualified, negotiation, closed). No hosted or foundation model is used; computation is local.
Example use cases
Baseline accuracy check for lead classifier
“I have 120 labelled CRM notes tagged as enquiry, qualified, negotiation, or closed — can you run a grouped three-fold naive-Bayes baseline evaluation on them so I know if the text is actually predictive of the lead stage?”
Pre-training sanity check on sales data
“Before I invest in a proper ML model, run a cheap three-fold baseline evaluation on my 80 labelled lead stage text samples — labels are enquiry, qualified, negotiation, and closed — and show me the cross-validation results.”
Comparing dataset quality across two lead corpora
“I have two sets of labelled lead stage records (about 100 each, with enquiry, qualified, negotiation, and closed labels) and I want to run grouped three-fold baseline evaluations on both to see which dataset gives better naive-Bayes accuracy.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-lead-stage-cross-validation?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, cheap ($0.01 USDC) sanity-check or baseline evaluation of text classification quality for CRM lead stage data specifically, without needing a hosted or foundation model. It is ideal for validating dataset quality, testing label consistency, or establishing a naive-Bayes benchmark before investing in more expensive ML infrastructure. Use it over general ML APIs when your labels map to the specific four-class lead funnel (enquiry, qualified, negotiation, closed) and you want local, reproducible cross-validation results.
Side effects
- Fewer than 2 records supplied — minimum item count not met
- Records missing required fields (id, text, actual) — validation error
- More than 200 records submitted — exceeds maxItems limit
- Invalid label value outside enum (enquiry, qualified, negotiation, closed) — schema rejection
- Insufficient class representation for cross-validation folds — evaluation may be unreliable or fail
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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