{
  "schema": "ml-prep/item@1",
  "item": {
    "id": "original-ml-metrics",
    "area": "machine-learning",
    "topic": "classification",
    "origin": "original",
    "title": "Classification metrics from counts",
    "skills": [
      "confusion-matrix",
      "precision-recall"
    ],
    "priority": "foundation",
    "difficulty": "easy",
    "estimated_minutes": 6,
    "prerequisites": [
      "fractions"
    ],
    "prompt": "A classifier has $\\mathrm{TP}=30$, $\\mathrm{FP}=10$, $\\mathrm{FN}=20$, and $\\mathrm{TN}=40$. Compute accuracy, precision, recall, and $F_1$.\n",
    "answer": "Accuracy is $0.70$, precision is $0.75$, recall is $0.60$, and\n\n$$F_1=\\frac{2(0.75)(0.60)}{0.75+0.60}=\\frac{2}{3}.$$\n",
    "check": {
      "kind": "numeric",
      "id": "original-ml-metrics",
      "values": [
        0.7,
        0.75,
        0.6,
        0.6666666666666666
      ]
    }
  }
}