class_docstr: Benchmarks for Lasso.
class_docstr_tok: ["Benchmarks","for","Lasso","."]
code: def skip(self, params):
      representation, precompute = params
  
      if representation == "sparse" and precompute is False:
          return True
      return False
  
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 5 for calling the LassoBenchmark obj's underlying member method code with example usage: obj.skip(params) and returns: False, True