code: def fit(self, dataset):
          
          dataset = dataset.map(_convert_to_vector)
          jmodel = callMLlibFunc("fitStandardScaler", self.withMean, self.withStd, dataset)
          return StandardScalerModel(jmodel)
docs: Computes the mean and variance and stores as a model to be used
          for later scaling.
  
          :param dataset: The data used to compute the mean and variance
                       to build the transformation model.
          :return: a StandardScalarModel