# Project Status Fixed-Holdout Learning Curve

> Project Status 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 labelled project-status text dataset using a naive-Bayes classifier, showing how model accuracy changes with training set size.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-project-status-learning-curve?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/project-status-fixed-holdout-learning-curve-67e2d130
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_-MMenPXc7AJfbCKE7pm2i

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability project-status-fixed-holdout-learning-curve-67e2d130 -d '<json body>'
```

Example prompt: Run a fixed-holdout learning curve on my project status dataset — I have about 80 labelled records where each entry has an ID, a short text description, and a label of either planned, active, blocked, or complete. I want to see how the naive-Bayes accuracy changes as training size grows.

## When to prefer this

Choose this endpoint when you need a quick, inexpensive ($0.01 USDC) learning curve evaluation for project status text classification using a naive-Bayes baseline, with up to 200 labelled records and a fixed holdout methodology. Prefer it over hosted model solutions when you want a lightweight, local-style benchmark without training a foundation model, and when your labels are specifically project-status categories (planned, active, blocked, complete).

## Known failure modes

- Fewer than 2 records supplied — minimum item count not met
- Records missing required fields (id, text, actual) — validation error
- Label values outside allowed enum (planned, active, blocked, complete) — schema rejection
- More than 200 records supplied — exceeds maxItems limit
- Text exceeds 1000-character limit per record — truncation or rejection
- Insufficient class diversity for meaningful holdout split — degenerate curve output
- Payment not completed via x402 protocol — request not processed

## How this service works

Project status - Fixed-holdout learning curve: Fixed-holdout learning curve 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 fixed-holdout learning curve deliverable.

## Output

Returns a fixed-holdout learning curve deliverable: a series of accuracy or performance metric values computed at increasing training set sizes using a naive-Bayes baseline on the supplied labelled text records, with the holdout evaluation set held constant throughout.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "records": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "id",
     "text",
     "actual"
    ],
    "properties": {
     "id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "text": {
      "type": "string",
      "default": "",
      "maxLength": 1000
     },
     "actual": {
      "enum": [
       "planned",
       "active",
       "blocked",
       "complete"
      ],
      "type": "string"
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "id": "example-0-0",
     "text": "planned sample document number 0 for this supplied dataset.",
     "actual": "planned"
    },
    {
     "id": "example-0-1",
     "text": "planned sample document number 1 for this supplied dataset.",
     "actual": "planned"
    },
    {
     "id": "example-0-2",
     "text": "planned sample document number 2 for this supplied dataset.",
     "actual": "planned"
    },
    {
     "id": "example-1-0",
     "text": "active sample document number 0 for this supplied dataset.",
     "actual": "active"
    },
    {
     "id": "example-1-1",
     "text": "active sample document number 1 for this supplied dataset.",
     "actual": "active"
    },
    {
     "id": "example-1-2",
     "text": "active sample document number 2 for this supplied dataset.",
     "actual": "active"
    },
    {
     "id": "example-2-0",
     "text": "blocked sample document number 0 for this supplied dataset.",
     "actual": "blocked"
    },
    {
     "id": "example-2-1",
     "text": "blocked sample document number 1 for this supplied dataset.",
     "actual": "blocked"
    },
    {
     "id": "example-2-2",
     "text": "blocked sample document number 2 for this supplied dataset.",
     "actual": "blocked"
    },
    {
     "id": "example-3-0",
     "text": "complete sample document number 0 for this supplied dataset.",
     "actual": "complete"
    },
    {
     "id": "example-3-1",
     "text": "complete sample document number 1 for this supplied dataset.",
     "actual": "complete"
    },
    {
     "id": "example-3-2",
     "text": "complete sample document number 2 for this supplied dataset.",
     "actual": "complete"
    }
   ],
   "maxItems": 200,
   "minItems": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/project-status-fixed-holdout-learning-curve-67e2d130/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)