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Commerce Intent Supplied-Group Evaluation
x402
Commerce Intent Supplied-Group Evaluation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).
Evaluates a supplied set of labelled commerce-intent text records (browse/purchase/return/other) broken down by group, returning per-group classification metrics and naive-Bayes baseline comparisons.
Price / call$0.01
Success—
StatusUnknown
How this service works
Commerce intent - Supplied-group evaluation: Supplied-group evaluation for Commerce intent. 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 supplied-group evaluation deliverable.
Output
A bounded deliverable containing per-group classification evaluation metrics for commerce intent labels (browse, purchase, return, other), including accuracy, confusion breakdown, and naive-Bayes baseline comparisons across the supplied group segments — derived entirely from the up-to-200 supplied records with no hosted model inference.
Example use cases
Segment accuracy audit for A/B test
“I ran an A/B test on my intent classifier and have predicted vs actual labels for two cohorts (group A and group B). Can you evaluate the results across both groups — each record has an ID, the text, the actual intent label (browse, purchase, return, or other), and the predicted label — so I can see where group B underperforms?”
Retail checkout intent model QA
“I need to QA my checkout intent model. I have 150 labelled product page texts with actual and predicted labels across three customer segments. Run a group-level evaluation and flag which segment has the worst purchase vs browse confusion.”
Return intent detection benchmarking
“Help me benchmark my return-intent classifier. I have a dataset of 180 customer messages labelled as browse, purchase, return, or other, split into two groups by geography. Evaluate the predictions against the actual labels per group and include a naive-Bayes baseline so I know if my model is actually adding value.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-commerce-intent-group-evaluation?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have your own labelled commerce-intent dataset (up to 200 records) with actual and predicted labels and want group-level evaluation metrics — particularly when you need a quick, low-cost ($0.01 USDC) local statistical assessment with a naive-Bayes baseline, without sending data to a large hosted model or incurring training costs. Prefer over general ML evaluation platforms when the task is specifically commerce intent (browse/purchase/return/other) and segmentation by group is a first-class requirement.
Side effects
- More than 200 records supplied — request rejected or truncated
- Missing required fields (id, text, actual, predicted, group) on any record — validation error
- Invalid enum value for actual or predicted (must be browse, purchase, return, or other) — schema rejection
- Empty records array — no metrics producible
- Record text exceeds 1000 characters — field truncated or rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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