code: function (strategy) {
          this.logger = Logger.getLogger("DecisionTree_js");
          var jvmObject;
          if (strategy instanceof Strategy) {
              jvmObject = new org.apache.spark.mllib.tree.DecisionTree(Utils.unwrapObject(strategy));
          } else if (strategy instanceof rg.apache.spark.mllib.tree.DecisionTree) {
              jvmObject = strategy;
          } else {
              throw "DecisionTree invalid constructor parameter"
          }
  
          JavaWrapper.call(this, jvmObject);
  
      }
docs: A class which implements a decision tree learning algorithm for classification and regression.
  It supports both continuous and categorical features.
  @param strategy The configuration parameters for the tree algorithm which specify the type
  of algorithm (classification, regression, etc.), feature type (continuous,
  categorical), depth of the tree, quantile calculation strategy, etc.
  @classdesc
   
  @param {module:eclairjs/mllib/tree/configuration.Strategy} strategy
  @class
  @memberof module:eclairjs/mllib/tree