class_docstr: Estimator for learning linear regressors by SVRG.
  
  Solves the following objective:
  
  .. code-block::
  
      minimize_w  1 / n_samples * \sum_i loss(w^T x_i, y_i)
                  + alpha * 0.5 * ||w||^2_2
code: def _get_loss(self):
      losses = {
          "squared": SquaredLoss(),
      }
      return losses[self.loss]
  
imports: import numpy
  from .base import BaseClassifier, BaseRegressor
  from .dataset_fast import get_dataset
  from .svrg_fast import _svrg_fit
  from .sgd_fast import ModifiedHuber
  from .sgd_fast import SmoothHinge
  from .sgd_fast import SquaredHinge
  from .sgd_fast import Log
  from .sgd_fast import SquaredLoss
label_desc: Use image node_id 2 for calling the SVRGRegressor obj's underlying member method code with example usage: obj._get_loss() and returns: losses