# Product Category Confusion Matrix

> Product Category Confusion Matrix 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).

Computes a confusion matrix for a product category classifier (apparel, home, electronics, other) from up to 200 labeled text records with actual and predicted labels.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-product-category-confusion?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/product-category-confusion-matrix-fc1ab25a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_75wmo5lRi4Y8MJOJbxtJH

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-confusion-matrix-fc1ab25a -d '<json body>'
```

Example prompt: I have 150 labeled product records where each one has an actual category (apparel, home, electronics, or other) and a predicted category from my classifier — can you compute a confusion matrix so I can see where it's getting confused?

## When to prefer this

Use this endpoint when you need a fast, inexpensive confusion matrix computation for a 4-class product category classifier (apparel, home, electronics, other) on a small labeled dataset of up to 200 records, without needing to train or host a model. Prefer this over general ML platforms when you want a single bounded deliverable at minimal cost via micropayment.

## Known failure modes

- More than 200 records supplied — request rejected or truncated
- Invalid or missing required fields (id, text, actual, predicted) on any record
- Actual or predicted values outside the allowed enum (apparel, home, electronics, other)
- Empty records array returns a trivial or error response
- Payment of 0.01 USDC not completed causes request rejection

## How this service works

Product category - Confusion matrix: Confusion matrix 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 confusion matrix deliverable.

## Output

A bounded confusion matrix deliverable showing counts of true positives, false positives, false negatives, and true negatives across the four product categories (apparel, home, electronics, other), summarizing where the classifier's predictions agree or diverge from actual labels.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "records": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "id",
     "text",
     "actual",
     "predicted"
    ],
    "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"
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "id": "example-0-0",
     "text": "apparel sample document number 0 for this supplied dataset.",
     "actual": "apparel",
     "predicted": "apparel"
    },
    {
     "id": "example-0-1",
     "text": "apparel sample document number 1 for this supplied dataset.",
     "actual": "apparel",
     "predicted": "apparel"
    },
    {
     "id": "example-0-2",
     "text": "apparel sample document number 2 for this supplied dataset.",
     "actual": "apparel",
     "predicted": "apparel"
    },
    {
     "id": "example-1-0",
     "text": "home sample document number 0 for this supplied dataset.",
     "actual": "home",
     "predicted": "home"
    },
    {
     "id": "example-1-1",
     "text": "home sample document number 1 for this supplied dataset.",
     "actual": "home",
     "predicted": "home"
    },
    {
     "id": "example-1-2",
     "text": "home sample document number 2 for this supplied dataset.",
     "actual": "home",
     "predicted": "home"
    },
    {
     "id": "example-2-0",
     "text": "electronics sample document number 0 for this supplied dataset.",
     "actual": "electronics",
     "predicted": "electronics"
    },
    {
     "id": "example-2-1",
     "text": "electronics sample document number 1 for this supplied dataset.",
     "actual": "electronics",
     "predicted": "electronics"
    },
    {
     "id": "example-2-2",
     "text": "electronics sample document number 2 for this supplied dataset.",
     "actual": "electronics",
     "predicted": "electronics"
    },
    {
     "id": "example-3-0",
     "text": "other sample document number 0 for this supplied dataset.",
     "actual": "other",
     "predicted": "other"
    },
    {
     "id": "example-3-1",
     "text":
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/product-category-confusion-matrix-fc1ab25a/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)