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Project Status Classifier — Macro, Micro & Weighted Aggregate Scores
x402
Project Status Classifier — Macro, Micro & Weighted Aggregate Scores 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).
Computes macro, micro, and weighted aggregate evaluation scores for a project-status text classifier using up to 200 labelled records with actual and predicted labels.
Price / call$0.01
Success—
StatusUnknown
How this service works
Project status - Macro micro and weighted scores: Macro micro and weighted scores for Project status. 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 macro micro and weighted scores deliverable.
Output
Returns macro, micro, and weighted aggregate classification scores (e.g. precision, recall, F1) computed across the four project status categories (planned, active, blocked, complete) for up to 200 supplied labelled text records.
Example use cases
Sprint classifier accuracy audit
“I've been using a Naive Bayes model to classify project tickets as planned, active, blocked, or complete. Can you run the macro, micro, and weighted evaluation scores against these 80 labelled test records so I can see where the model is struggling?”
Comparing two model checkpoints
“I have 120 labelled project status records with actual and predicted labels from my latest model checkpoint — can you compute the macro, micro, and weighted aggregate scores so I can compare it against last week's baseline?”
Reporting classifier quality to stakeholders
“Before I share the project status prediction tool with the team, I need the macro, micro, and weighted scores across all four statuses — planned, active, blocked, complete — using these 200 sample records with ground truth labels.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-project-status-aggregate-scores?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, low-cost ($0.01 USDC) aggregate evaluation of a project-status text classifier using your own labelled dataset without hosting a model or invoking a foundation model. It is best suited for local dataset evaluation, spot-checking classifier quality, or generating baseline metrics across the four project status categories.
Side effects
- Exceeding 200 records limit causes rejection
- Missing required fields (id, text, actual, predicted) cause validation errors
- Invalid label values outside the enum (planned, active, blocked, complete) cause schema errors
- Empty records array returns no meaningful scores
- Highly imbalanced datasets may produce misleading macro scores
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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