code: function(lambda) {
          var jvmObject;
          this.logger = Logger.getLogger("NaiveBayes_js");
          if (lambda instanceof org.apache.spark.mllib.classification.NaiveBayes) {
              jvmObject = lambda;
          } else if (lambda) {
              jvmObject = new org.apache.spark.mllib.classification.NaiveBayes(lambda);
          } else {
              jvmObject = new org.apache.spark.mllib.classification.NaiveBayes();
          }
  
  
           JavaWrapper.call(this, jvmObject);
  
      }
docs: Trains a Naive Bayes model given an RDD of `(label, features)` pairs.
  
  This is the Multinomial NB ([[http://tinyurl.com/lsdw6p]]) which can handle all kinds of
  discrete data.  For example, by converting documents into TF-IDF vectors, it can be used for
  document classification.  By making every vector a 0-1 vector, it can also be used as
  Bernoulli NB ([[http://tinyurl.com/p7c96j6]]). The input feature values must be nonnegative.
  @memberof module:eclairjs/mllib/classification
  @classdesc
  @param {number} lambda
  @class