code: function (weights, intercept) {
          var jvmObject;
          if (arguments[0] instanceof org.apache.spark.mllib.classification.SVMModel) {
              jvmObject = arguments[0];
          } else {
              jvmObject = new org.apache.spark.mllib.classification.SVMModel(Utils.unwrapObject(weights), intercept);
          }
  
          this.logger = Logger.getLogger("SVMModel_js");
          ClassificationModel.call(this, jvmObject);
  
      }
docs: Model for Support Vector Machines (SVMs).
  
  @param weights Weights computed for every feature.
  @param intercept Intercept computed for this model.
  @memberof module:eclairjs/mllib/classification
  @classdesc
  @param {module:eclairjs/mllib/linalg.Vector} weights
  @param {float} intercept
  @class