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Task Type Grouped Dataset Split
x402
Task Type Grouped Dataset Split 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).
Performs a grouped dataset split on up to 200 labelled task-type text records, returning train/test partitions with local evaluation and naive-Bayes baseline metrics.
Price / call$0.01
Success—
StatusUnknown
How this service works
Task type - Grouped dataset split: Grouped dataset split for Task type. 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 dataset split deliverable.
Output
A grouped dataset split deliverable containing train and test partitions of the supplied labelled records, organized by task type class (research, writing, analysis, implementation), along with local evaluation metrics and a naive-Bayes baseline benchmark score.
Example use cases
Prototype task classifier evaluation
“I have 80 labelled documents tagged as research, writing, analysis, or implementation — can you do a grouped dataset split on them and show me the naive-Bayes baseline performance?”
Validate annotation balance across task types
“Here are 120 annotated task-type records; run a grouped split so I can check whether each class (research, writing, analysis, implementation) is evenly represented across train and test sets.”
Prepare ML training data for task routing
“I need to split my 150 labelled task-description records — research, writing, analysis, and implementation — into grouped train and test partitions so I can start building a task-routing classifier.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-task-type-dataset-split?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a small labelled text dataset (up to 200 records) tagged with task-type categories (research, writing, analysis, implementation) and need a grouped train/test split with a quick naive-Bayes baseline evaluation — without needing a hosted model or large foundation model. Ideal for prototyping text classifiers, validating annotation balance, or benchmarking simple baselines locally before investing in heavier ML infrastructure.
Side effects
- Fewer than 2 records supplied — minimum input not met, request rejected
- More than 200 records supplied — exceeds maxItems limit, request rejected
- Record text exceeds 1000 characters — field validation error
- Invalid or missing 'actual' label not in enum (research/writing/analysis/implementation) — schema validation failure
- Insufficient records per class to produce a meaningful grouped split — degraded or empty partition output
- Payment not completed — x402 payment required before response is returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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