class_docstr: Benchmark for SGD
class_docstr_tok: ["Benchmark","for","SGD"]
code: def make_data(self, params):
      (representation,) = params
  
      if representation == "dense":
          data = _synth_regression_dataset(
              n_samples=100000, n_features=200
          )
      else:
          data = _synth_regression_sparse_dataset(
              n_samples=100000, n_features=1000, density=0.01
          )
  
      return data
  
imports: from sklearn.linear_model import ElasticNet, Lasso, LinearRegression, LogisticRegression, Ridge, SGDRegressor
  from .common import Benchmark, Estimator, Predictor
  from .datasets import _20newsgroups_highdim_dataset, _20newsgroups_lowdim_dataset, _synth_regression_dataset, _synth_regression_sparse_dataset
  from .utils import make_gen_classif_scorers, make_gen_reg_scorers
label_desc: Use image node_id 2 for calling the SGDRegressorBenchmark obj's underlying member method code with example usage: obj.make_data(params) and returns: data