# Product Category Classifier — Macro, Micro & Weighted Scores

> Product Category Classifier — Macro, Micro & Weighted Scores 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 macro, micro, and weighted aggregate evaluation scores for a product category classifier (apparel, home, electronics, other) given up to 200 labelled text records with actual and predicted labels.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-product-category-aggregate-scores?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-classifier-macro-micro-weighted-scores-35993184
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_kK8fRysh1U2EZ6IiZ4BKr

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-classifier-macro-micro-weighted-scores-35993184 -d '<json body>'
```

Example prompt: I ran my product category classifier on 150 items tagged as apparel, home, electronics, or other — can you compute the macro, micro, and weighted aggregate scores comparing the actual labels to what the model predicted?

## When to prefer this

Choose this endpoint when you need a quick, cheap ($0.01 USDC) aggregate evaluation of a product category classifier with macro, micro, and weighted scoring on a small labelled dataset (up to 200 records) without standing up your own evaluation infrastructure or calling a large foundation model.

## Known failure modes

- More than 200 records supplied — request rejected or truncated
- Missing required fields (id, text, actual, predicted) in any record — validation error
- Invalid enum value for actual or predicted (must be apparel, home, electronics, or other) — schema error
- Empty records array — no metrics computable
- Payment not included or insufficient USDC — 402 payment required response

## How this service works

Product category - Macro micro and weighted scores: Macro micro and weighted scores 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 macro micro and weighted scores deliverable.

## Output

Returns macro, micro, and weighted aggregate classification scores (such as precision, recall, and F1) computed across up to 200 supplied text records with actual and predicted product category labels (apparel, home, electronics, other).

## 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-classifier-macro-micro-weighted-scores-35993184/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)