{
  "kind": "illustrative-browser-calculation",
  "task": "Signal denoising",
  "metric": "mean squared error; lower is better",
  "rule": "Accept a change only if the held-out error drops as well as the training error.",
  "training": {
    "measured": [
      2,
      4,
      3,
      5,
      8,
      6,
      9
    ],
    "reference": [
      2,
      3,
      4,
      5,
      6,
      7,
      8
    ]
  },
  "heldOut": {
    "measured": [
      4,
      2,
      6,
      5,
      9,
      7,
      8
    ],
    "reference": [
      3,
      4,
      5,
      6,
      7,
      8,
      9
    ]
  },
  "baseline": {
    "method": "identity",
    "training": {
      "output": [
        2,
        4,
        3,
        5,
        8,
        6,
        9
      ],
      "error": 1.1428571428571428
    },
    "heldOut": {
      "output": [
        4,
        2,
        6,
        5,
        9,
        7,
        8
      ],
      "error": 1.8571428571428572
    }
  },
  "candidate": {
    "method": "mean of each measurement and its available immediate neighbors",
    "training": {
      "output": [
        3,
        3,
        4,
        5.333333333333333,
        6.333333333333333,
        7.666666666666667,
        7.5
      ],
      "error": 0.27380952380952384
    },
    "heldOut": {
      "output": [
        3,
        4,
        4.333333333333333,
        6.666666666666667,
        7,
        8,
        7.5
      ],
      "error": 0.44841269841269854
    },
    "decision": "accepted"
  },
  "shortcut": {
    "method": "copy the training answers; pass any other value through unchanged",
    "training": {
      "output": [
        2,
        3,
        4,
        5,
        6,
        7,
        8
      ],
      "error": 0
    },
    "heldOut": {
      "output": [
        3,
        2,
        7,
        5,
        8,
        7,
        6
      ],
      "error": 2.857142857142857
    },
    "decision": "rejected"
  },
  "limitation": "Two small sets of seven points each. This is not a product benchmark or evidence that the method generalizes."
}