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Training Question Classifier — Macro, Micro & Weighted F1 Scores
x402
Training Question Classifier — Macro, Micro & Weighted F1 Scores is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-12).
Computes macro, micro, and weighted aggregate classification scores (precision, recall, F1) for a set of labelled training question records with actual vs. predicted categories.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training question - Macro micro and weighted scores: Macro micro and weighted scores for Training question. 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-averaged, micro-averaged, and weighted-averaged precision, recall, and F1 scores computed over the supplied labelled records, with class labels spanning concept, procedure, example, and assessment. The output is a bounded, single-deliverable evaluation summary for the provided dataset.
Example use cases
Evaluating a question-type classifier model
“I've got 150 training question records where each one has the actual label (concept, procedure, example, or assessment) and what my classifier predicted — can you calculate the macro, micro, and weighted F1 scores so I can evaluate how well it's doing?”
Comparing two labelling approaches
“I ran two different labelling passes on my training question dataset and want to check the macro, micro, and weighted scores for one of them — here are 120 records with actual and predicted labels across concept, procedure, example, and assessment categories.”
Quality check before model submission
“Before I submit my question classifier, I need to verify its aggregate performance — can you take these 80 labelled records with actual and predicted labels and give me the macro, micro, and weighted precision, recall, and F1 breakdown?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-training-question-aggregate-scores?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, on-demand aggregate classification metrics (macro, micro, weighted F1) for a small labelled dataset of training question records categorised as concept, procedure, example, or assessment — without needing to host a model or use a foundation model training service. Ideal for rapid evaluation loops on datasets up to 200 records at minimal cost ($0.01 USDC).
Side effects
- Too many records supplied (over 200 limit) — request rejected
- Missing required fields (id, text, actual, predicted) on any record — validation error
- Invalid label values outside the enum (concept, procedure, example, assessment) — schema error
- Empty records array — no scores can be computed
- Malformed JSON input — parse error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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