Spec

Extraits de code

curl "https://api.oanor.com/classifier-api/v1/meta" \
  -H "x-oanor-key: oanor_test_..."

await fetch("https://api.oanor.com/classifier-api/v1/meta", {
  headers: { "x-oanor-key": "oanor_test_..." }
});

$ch = curl_init("https://api.oanor.com/classifier-api/v1/meta");
curl_setopt($ch, CURLOPT_HTTPHEADER, ["x-oanor-key: oanor_test_..."]);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
$out = curl_exec($ch);

import requests
requests.get(
    "https://api.oanor.com/classifier-api/v1/meta",
    headers={"x-oanor-key": "oanor_test_..."}
)

Exemple de réponse

Une réponse réelle de ce endpoint, capturée lors du dernier contrôle de santé.

{
    "data": {
        "notes": "Counts are non-negative integers; rates and probabilities are 0–1. Metrics with a zero denominator are returned as null.",
        "service": "classifier-api",
        "formulae": {
            "f1": "2·P·R/(P+R)",
            "mcc": "(TP·TN − FP·FN)/√((TP+FP)(TP+FN)(TN+FP)(TN+FN))",
            "ppv": "(sens·prev)/(sens·prev + (1−spec)(1−prev))",
            "recall": "TP/(TP+FN)",
            "precision": "TP/(TP+FP)"
        },
        "endpoints": {
            "GET /v1/meta": "This document.",
            "GET /v1/fbeta": "F-beta score from precision & recall (or tp/fp/fn) for any beta.",
            "GET /v1/confusion": "Accuracy, precision, recall, F1, MCC and more from tp/fp/fn/tn.",
            "GET /v1/diagnostic": "PPV, NPV and likelihood ratios from sensitivity, specificity and prevalence."
        },
        "description": "Classifier-evaluation metrics: a full metric suite from a confusion matrix, Bayesian diagnostic-test statistics (PPV/NPV, likelihood ratios), and the F-beta score."
    },
    "meta": {
        "timestamp": "2026-06-05T03:09:02.760Z",
        "request_id": "d0e26edb-baa4-4c53-8da7-649522f850b6"
    },
    "status": "ok",
    "message": "Meta",
    "success": true
}