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Task Type Fixed-Holdout Learning Curve
x402
Task Type Fixed-Holdout Learning Curve 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).
Generates a fixed-holdout learning curve for a naive-Bayes text classifier that predicts task type (research, writing, analysis, implementation) from up to 200 labelled text records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Task type - Fixed-holdout learning curve: Fixed-holdout learning curve 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 fixed-holdout learning curve deliverable.
Output
A bounded fixed-holdout learning curve deliverable showing how naive-Bayes classification accuracy on the held-out test set changes as the number of training examples increases, computed locally from the supplied labelled text records across the four task type categories.
Example use cases
Estimating data needs for task classifier
“I have 80 labelled documents — some tagged as research, some as writing, analysis, or implementation — and I want a learning curve showing how a naive-Bayes classifier improves as I add more training examples. Can you run the fixed-holdout evaluation for me?”
Benchmarking classifier before scaling labelling effort
“Before I pay people to label thousands of documents by task type, can you run a learning curve on my existing 120 labelled records to see if accuracy plateaus early? The labels are research, writing, analysis, and implementation.”
Comparing classification difficulty across task types
“I've got 150 text snippets labelled as research, writing, analysis, or implementation and I want to understand how well a simple classifier separates them — can you generate a fixed-holdout learning curve so I can see where it struggles?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-task-type-learning-curve?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a small set of labelled text documents (up to 200) classified into task types (research, writing, analysis, implementation) and want to understand how classifier performance scales with training data using a simple naive-Bayes baseline — without needing a hosted model or foundation model. Ideal for feasibility checks before investing in larger labelling efforts.
Side effects
- Fewer than 2 records supplied — minimum input requirement not met
- Record text exceeds 1000 character limit — truncation or rejection
- Invalid or missing 'actual' label not in enum (research, writing, analysis, implementation)
- Too few examples per class to construct a meaningful learning curve
- Duplicate or missing record IDs causing data integrity issues
- Payment not processed — x402 payment required before response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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