# Product Category Confidence Calibration Bins

> Product Category Confidence Calibration Bins 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).

Computes confidence calibration bins for a product category classifier (apparel, home, electronics, other) given up to 200 labelled prediction records with class probabilities.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-product-category-calibration?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/product-category-confidence-calibration-bins-a47c1e49
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_y-g6J1nLHfbstO2yxQl5O

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 product-category-confidence-calibration-bins-a47c1e49 -d '<json body>'
```

Example prompt: Compute confidence calibration bins for my product category classifier — I have 50 labelled records where each has the text, the actual category (apparel, home, electronics, or other), the predicted category, and a 4-element probability array. Can you run the calibration analysis on those?

## When to prefer this

Choose this endpoint when you need calibration bin statistics specifically for a 4-class product category classifier (apparel, home, electronics, other) and have up to 200 labelled prediction records with probability vectors. It is a lightweight, pay-per-call option suitable for spot-checking model calibration without setting up local evaluation infrastructure or training a new model.

## Known failure modes

- More than 200 records supplied — request rejected or truncated
- Probability arrays not summing to 1 or containing values outside [0,1] — validation error
- Fewer than 4 probability values per record — schema validation failure
- Unknown class label outside enum (apparel, home, electronics, other) — rejected
- Empty records array — insufficient data error

## How this service works

Product category - Confidence calibration bins: Confidence calibration bins for Product category. 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 confidence calibration bins deliverable.

## Output

Returns confidence calibration bins for the product category classifier — bin boundaries, mean predicted probability per bin, actual accuracy per bin, and sample counts — enabling reliability diagram construction and identification of over- or under-confidence regions.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "records": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "id",
     "text",
     "actual",
     "predicted",
     "probabilities"
    ],
    "properties": {
     "id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "text": {
      "type": "string",
      "default": "",
      "maxLength": 1000
     },
     "actual": {
      "enum": [
       "apparel",
       "home",
       "electronics",
       "other"
      ],
      "type": "string"
     },
     "predicted": {
      "enum": [
       "apparel",
       "home",
       "electronics",
       "other"
      ],
      "type": "string"
     },
     "probabilities": {
      "type": "array",
      "items": {
       "type": "number",
       "default": 0,
       "maximum": 1,
       "minimum": 0
      },
      "default": [],
      "maxItems": 4,
      "minItems": 4
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "id": "example-0-0",
     "text": "apparel sample document number 0 for this supplied dataset.",
     "actual": "apparel",
     "predicted": "apparel",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-1",
     "text": "apparel sample document number 1 for this supplied dataset.",
     "actual": "apparel",
     "predicted": "apparel",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-2",
     "text": "apparel sample document number 2 for this supplied dataset.",
     "actual": "apparel",
     "predicted": "apparel",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-0",
     "text": "home sample document number 0 for this supplied dataset.",
     "actual": "home",
     "predicted": "home",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-1",
     "text": "home sample document number 1 for this supplied dataset.",
     "actual": "home",
     "predicted": "home",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-2",
     "text"
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/product-category-confidence-calibration-bins-a47c1e49/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)