Method train

src/cross-validate.js:81–159

* * @param {object} data * @param {object} trainOpts * @param {number} [k] * @returns { * { * avgs: { * error: number, * trainTime: number, * testTime: number, * iterations: number, * trainError: number * }, * stats: { *

(data, trainOpts = {}, k = 4)

   * }
   */
  train(data, trainOpts = {}, k = 4) {
    if (data.length <= k) {
      throw new Error(`Training set size is too small for ${ data.length } k folds of ${ k }`);
    }
    let size = data.length / k;

    if (data.constructor === Array) {
      this.shuffleArray(data);
    } else {
      let newData = {};
      this.shuffleArray(Object.keys(data)).forEach((key) => {
        newData[key] = data[key];
      });
      data = newData;
    }

    let avgs = {
      error: 0,
      trainTime: 0,
      testTime: 0,
      iterations: 0,
      trainError: 0
    };

    let stats = {
      truePos: 0,
      trueNeg: 0,
      falsePos: 0,
      falseNeg: 0,
      total: 0
    };

    let results = [];
    let stat;
    let sum;

    for (let i = 0; i < k; i++) {
      let dclone = data.slice(0);
      let testSet = dclone.splice(i * size, size);
      let trainSet = dclone;
      let result = this.testPartition(trainOpts, trainSet, testSet);
      for (stat in avgs) {
        if (stat in avgs) {
          sum = avgs[stat];
          avgs[stat] = sum + result[stat];
        }
      }

      for (stat in stats) {
        if (stat in stats) {
          sum = stats[stat];
          stats[stat] = sum + result[stat];
        }
      }

      results.push(result);
    }