# Ticket Priority Fixed-Holdout Learning Curve

> Ticket Priority 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 2026-10-16).

Generates a fixed-holdout learning curve for a ticket priority classifier (low/normal/high) using up to 200 labelled text records and a naive-Bayes baseline.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-ticket-priority-learning-curve?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/ticket-priority-fixed-holdout-learning-curve-61f4a0b3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_HW7vfse5MpM9LqXNDFHPc

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 ticket-priority-fixed-holdout-learning-curve-61f4a0b3 -d '<json body>'
```

Example prompt: Run a fixed-holdout learning curve for my ticket priority classifier using these labelled support tickets — each ticket has an ID, the ticket text, and its actual priority (low, normal, or high) — I've got about 120 records and want to see how classification performance changes as training size grows.

## When to prefer this

Choose this endpoint when you have up to 200 labelled support ticket texts with low/normal/high priority labels and want to understand how classifier performance scales with training data size using a lightweight naive-Bayes model — no hosted model or foundation model required. Ideal for early-stage data assessment, data sufficiency analysis, and local benchmarking before committing to larger ML pipelines.

## Known failure modes

- Fewer than 2 records supplied — minimum input not met
- Records missing required fields (id, text, actual) — validation error
- More than 200 records supplied — exceeds maxItems limit
- Invalid priority label (not low/normal/high) — enum validation failure
- Text field exceeds 1000 characters per record — truncation or rejection
- Insufficient class representation to form a meaningful holdout split

## How this service works

Ticket priority - Fixed-holdout learning curve: Fixed-holdout learning curve for Ticket priority. 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 showing how classification performance (accuracy or related metrics) changes as the number of training examples increases, computed using a naive-Bayes baseline on the supplied labelled ticket text records split with a fixed holdout. Includes evaluation metrics across training-size increments.

## 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": [
       "low",
       "normal",
       "high"
      ],
      "type": "string"
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "id": "example-0-0",
     "text": "low sample document number 0 for this supplied dataset.",
     "actual": "low"
    },
    {
     "id": "example-0-1",
     "text": "low sample document number 1 for this supplied dataset.",
     "actual": "low"
    },
    {
     "id": "example-0-2",
     "text": "low sample document number 2 for this supplied dataset.",
     "actual": "low"
    },
    {
     "id": "example-1-0",
     "text": "normal sample document number 0 for this supplied dataset.",
     "actual": "normal"
    },
    {
     "id": "example-1-1",
     "text": "normal sample document number 1 for this supplied dataset.",
     "actual": "normal"
    },
    {
     "id": "example-1-2",
     "text": "normal sample document number 2 for this supplied dataset.",
     "actual": "normal"
    },
    {
     "id": "example-2-0",
     "text": "high sample document number 0 for this supplied dataset.",
     "actual": "high"
    },
    {
     "id": "example-2-1",
     "text": "high sample document number 1 for this supplied dataset.",
     "actual": "high"
    },
    {
     "id": "example-2-2",
     "text": "high sample document number 2 for this supplied dataset.",
     "actual": "high"
    }
   ],
   "maxItems": 200,
   "minItems": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/ticket-priority-fixed-holdout-learning-curve-61f4a0b3/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)