docstr: ...Test LogisticRegression basic settings
          
docstr_tok: ["...","Test","LogisticRegression","basic","settings"]
code: def test_LogisticRegression_settings(self):
      """...Test LogisticRegression basic settings"""
      # solver
      from tick.solver import AGD, GD, BFGS, SGD, SVRG, SDCA
  
      solver_class_map = {
          "gd": GD,
          "agd": AGD,
          "sgd": SGD,
          "svrg": SVRG,
          "bfgs": BFGS,
          "sdca": SDCA,
      }
      for solver in solvers:
          learner = LogisticRegression(
              solver=solver, **Test.specific_solver_kwargs(solver)
          )
          solver_class = solver_class_map[solver]
          self.assertTrue(isinstance(learner._solver_obj, solver_class))
  
      msg = (
          "^``solver`` must be one of agd, bfgs, gd, sdca, sgd, "
          "svrg, got wrong_name$"
      )
      with self.assertRaisesRegex(ValueError, msg):
          LogisticRegression(solver="wrong_name")
  
      # prox
      prox_class_map = {
          "none": ProxZero,
          "l1": ProxL1,
          "l2": ProxL2Sq,
          "elasticnet": ProxElasticNet,
          "tv": ProxTV,
          "binarsity": ProxBinarsity,
      }
      for penalty in penalties:
          if penalty == "binarsity":
              learner = LogisticRegression(
                  penalty=penalty, blocks_start=[0], blocks_length=[1]
              )
          else:
              learner = LogisticRegression(penalty=penalty)
          prox_class = prox_class_map[penalty]
          self.assertTrue(isinstance(learner._prox_obj, prox_class))
  
      msg = (
          "^``penalty`` must be one of binarsity, elasticnet, l1, l2, none, "
          "tv, got wrong_name$"
      )
      with self.assertRaisesRegex(ValueError, msg):
          LogisticRegression(penalty="wrong_name")
  
imports: import itertools
  import unittest
  import numpy
  from sklearn.metrics import roc_auc_score
  from tick.base.inference import InferenceTest
  from tick.linear_model import SimuLogReg, LogisticRegression
  from tick.simulation import weights_sparse_gauss
  from tick.preprocessing.features_binarizer import FeaturesBinarizer
  from tick.prox import ProxZero, ProxL1, ProxL2Sq, ProxElasticNet, ProxTV, ProxBinarsity
label_desc: Use image node_id 6 for calling the Test obj's underlying member method code with example usage: obj.test_LogisticRegression_settings() without return types