Method _validateTrainingOptions

src/neural-network.js:47–64

* * @param options * @private

(options)

   * @private
   */
  static _validateTrainingOptions(options) {
    const validations = {
      iterations: (val) => { return typeof val === 'number' && val > 0; },
      errorThresh: (val) => { return typeof val === 'number' && val > 0 && val < 1; },
      log: (val) => { return typeof val === 'function' || typeof val === 'boolean'; },
      logPeriod: (val) => { return typeof val === 'number' && val > 0; },
      learningRate: (val) => { return typeof val === 'number' && val > 0 && val < 1; },
      momentum: (val) => { return typeof val === 'number' && val > 0 && val < 1; },
      callback: (val) => { return typeof val === 'function' || val === null },
      callbackPeriod: (val) => { return typeof val === 'number' && val > 0; },
      timeout: (val) => { return typeof val === 'number' && val > 0 }
    };
    Object.keys(NeuralNetwork.trainDefaults).forEach(key => {
      if (validations.hasOwnProperty(key) && !validations[key](options[key])) {
        throw new Error(`[${key}, ${options[key]}] is out of normal training range, your network will probably not train.`);
      }
    });
  }

  constructor(options = {}) {
    Object.assign(this, this.constructor.defaults, options);