# Return Reason Classifier – Grouped Three-Fold Cross-Validation

> Return Reason Classifier – Grouped Three-Fold Cross-Validation 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).

Runs a grouped three-fold cross-validation baseline evaluation on up to 200 labelled return-reason text records using a naive-Bayes classifier, returning accuracy and fold metrics.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-cross-validation?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/return-reason-classifier-grouped-three-fold-cross-validation-f200de4d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_0wzpYx7mly8NEF_iLZ2mE

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 return-reason-classifier-grouped-three-fold-cross-validation-f200de4d -d '<json body>'
```

Example prompt: Run a grouped three-fold cross-validation baseline on these 150 labelled return-reason records I have — each one has an ID, the customer's return comment text, and the actual label (damaged, wrong_item, unwanted, or other) — and tell me what accuracy the naive-Bayes baseline achieves across the folds.

## When to prefer this

Choose this endpoint when you need a cheap, fast, local baseline cross-validation for a return-reason text classification task with up to 200 labelled examples and four fixed categories (damaged, wrong_item, unwanted, other). It is ideal for sanity-checking label quality or annotation consistency before committing to larger model training. Prefer alternatives if you need foundation-model training, hosted inference, more than 200 records, or categories beyond the four supported labels.

## Known failure modes

- Fewer than 2 records supplied — minimum input not met
- More than 200 records supplied — exceeds maximum batch size
- Invalid or missing 'actual' label not in enum (damaged, wrong_item, unwanted, other)
- Records with empty or missing 'text' field cause validation errors
- Insufficient class diversity for meaningful three-fold grouping
- Payment not completed — x402 micropayment of 0.01 USDC required per call

## How this service works

Return reason - Grouped three-fold baseline evaluation: Grouped three-fold baseline evaluation for Return reason. 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 three-fold baseline evaluation deliverable.

## Output

Returns a grouped three-fold cross-validation result for the supplied labelled return-reason dataset, including per-fold and aggregate accuracy metrics produced by a local naive-Bayes baseline classifier. No hosted model is involved; the computation is self-contained and deterministic for the supplied records.

## 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": [
       "damaged",
       "wrong_item",
       "unwanted",
       "other"
      ],
      "type": "string"
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "id": "example-0-0",
     "text": "damaged sample document number 0 for this supplied dataset.",
     "actual": "damaged"
    },
    {
     "id": "example-0-1",
     "text": "damaged sample document number 1 for this supplied dataset.",
     "actual": "damaged"
    },
    {
     "id": "example-0-2",
     "text": "damaged sample document number 2 for this supplied dataset.",
     "actual": "damaged"
    },
    {
     "id": "example-1-0",
     "text": "wrong_item sample document number 0 for this supplied dataset.",
     "actual": "wrong_item"
    },
    {
     "id": "example-1-1",
     "text": "wrong_item sample document number 1 for this supplied dataset.",
     "actual": "wrong_item"
    },
    {
     "id": "example-1-2",
     "text": "wrong_item sample document number 2 for this supplied dataset.",
     "actual": "wrong_item"
    },
    {
     "id": "example-2-0",
     "text": "unwanted sample document number 0 for this supplied dataset.",
     "actual": "unwanted"
    },
    {
     "id": "example-2-1",
     "text": "unwanted sample document number 1 for this supplied dataset.",
     "actual": "unwanted"
    },
    {
     "id": "example-2-2",
     "text": "unwanted sample document number 2 for this supplied dataset.",
     "actual": "unwanted"
    },
    {
     "id": "example-3-0",
     "text": "other sample document number 0 for this supplied dataset.",
     "actual": "other"
    },
    {
     "id": "example-3-1",
     "text": "other sample document number 1 for this supplied dataset.",
     "actual": "other"
    },
    {
     "id": "example-3-2",
     "text": "other sample document number 2 for this supplied dataset.",
     "actual": "other"
    }
   ],
   "maxItems": 200,
   "minItems": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/return-reason-classifier-grouped-three-fold-cross-validation-f200de4d/health.json
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