Function renderEvaluateTable

iris-fitDataset/ui.js:119–146

(xData, yTrue, yPred, logits)

}

export function renderEvaluateTable(xData, yTrue, yPred, logits) {
  const tableBody = document.getElementById('evaluate-tbody');

  for (let i = 0; i < yTrue.length; ++i) {
    const row = document.createElement('tr');
    for (let j = 0; j < 4; ++j) {
      const cell = document.createElement('td');
      cell.textContent = xData[4 * i + j].toFixed(1);
      row.appendChild(cell);
    }
    const truthCell = document.createElement('td');
    truthCell.textContent = IRIS_CLASSES[yTrue[i]];
    row.appendChild(truthCell);
    const predCell = document.createElement('td');
    predCell.textContent = IRIS_CLASSES[yPred[i]];
    predCell.classList =
        yPred[i] === yTrue[i] ? ['correct-prediction'] : ['wrong-prediction'];
    row.appendChild(predCell);
    const logitsCell = document.createElement('td');
    const exampleLogits =
        logits.slice(i * IRIS_NUM_CLASSES, (i + 1) * IRIS_NUM_CLASSES);
    logitsToSpans(exampleLogits).map(logitSpan => {
      logitsCell.appendChild(logitSpan);
    });
    row.appendChild(logitsCell);
    tableBody.appendChild(row);
  }
}

export function wireUpEvaluateTableCallbacks(predictOnManualInputCallback) {
  const petalLength = document.getElementById('petal-length');