class_docstr: Intent classifier using the Logistic Regression.
docstr: Components that should be included in the pipeline before this component.
docstr_tok: ["Components","that","should","be","included","in","the","pipeline","before","this","component","."]
code: def required_components(cls) -> List[Type]:
      """Components that should be included in the pipeline before this component."""
      return [Featurizer]
  
imports: import logging
  from typing import Any, Text, Dict, List, Type, Tuple
  import joblib
  from scipy.sparse import hstack, vstack, csr_matrix
  from sklearn.linear_model import LogisticRegression
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.graph import ExecutionContext, GraphComponent
  from rasa.nlu.classifiers import LABEL_RANKING_LENGTH
  from rasa.nlu.featurizers.featurizer import Featurizer
  from rasa.nlu.classifiers.classifier import IntentClassifier
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.nlu.constants import TEXT, INTENT
  from rasa.utils.tensorflow.constants import RANKING_LENGTH
label_desc: Use image node_id 1 for calling the LogisticRegressionClassifier obj's underlying member method code with example usage: obj.required_components(cls) and returns: list