code: function (boundaries, predictions, isotonic) {
          this.logger = Logger.getLogger("IsotonicRegressionModel_js");
          var jvmObject;
          if (boundaries instanceof org.apache.spark.mllib.regression.IsotonicRegressionModel) {
              jvmObject = boundaries;
          } else {
              jvmObject = new org.apache.spark.mllib.regression.IsotonicRegressionModel(boundaries, predictions, isotonic);
          }
  
          JavaWrapper.call(this, jvmObject);
  
      }
docs: Regression model for isotonic regression.
  
  @param boundaries Array of boundaries for which predictions are known.
  Boundaries must be sorted in increasing order.
  @param predictions Array of predictions associated to the boundaries at the same index.
  Results of isotonic regression and therefore monotone.
  @param isotonic indicates whether this is isotonic or antitonic.
  
  @memberof module:eclairjs/mllib/regression
  @classdesc
   
  @param {float[]} boundaries
  @param {float[]} predictions
  @param {boolean} isotonic
  @class