class_docstr: Linear model (scikit-learn): https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html
  
  Model backend differs depending on problem_type:
  
      'binary' & 'multiclass': https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html
  
      'regression': https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html#sklearn.linear_model.Ridge
code: def _select_features_handle_text_ignore(
      self,
      df,
      categorical_featnames,
      language_featnames,
      continuous_featnames,
      bool_featnames,
  ):
      types_of_features = dict()
      types_of_features.update(
          self._select_continuous(df, continuous_featnames)
      )
      types_of_features.update(self._select_bool(df, bool_featnames))
      types_of_features.update(
          self._select_categorical(df, categorical_featnames)
      )
      return types_of_features
  
imports: import logging
  import re
  import time
  import warnings
  from collections import defaultdict
  import numpy
  from sklearn.compose import ColumnTransformer
  from sklearn.feature_extraction.text import TfidfVectorizer
  from sklearn.impute import SimpleImputer
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import QuantileTransformer, StandardScaler
  from autogluon.common.features.types import R_BOOL, R_CATEGORY, R_FLOAT, R_INT, R_OBJECT, S_BOOL, S_TEXT_AS_CATEGORY
  from autogluon.core.constants import BINARY, REGRESSION
  from autogluon.core.models import AbstractModel
  from autogluon.core.utils.exceptions import TimeLimitExceeded
  from .hyperparameters.parameters import IGNORE, INCLUDE, ONLY, _get_solver, get_param_baseline, preprocess_params_set
  from .hyperparameters.searchspaces import get_default_searchspace
  from .lr_preprocessing_utils import NlpDataPreprocessor, OheFeaturesGenerator
label_desc: Use image node_id 13 for calling the LinearModel obj's underlying member method code with example usage: obj._select_features_handle_text_ignore(df, categorical_featnames, language_featnames, continuous_featnames, bool_featnames) and returns: types_of_features