class_docstr: Intent classifier using the Logistic Regression.
docstr: Construct a new classifier.
docstr_tok: ["Construct","a","new","classifier","."]
code: def __init__(
      self,
      config: Dict[Text, Any],
      name: Text,
      model_storage: ModelStorage,
      resource: Resource,
  ) -> None:
      """Construct a new classifier."""
      self.name = name
      self.config = {**self.get_default_config(), **config}
      self.clf = LogisticRegression(
          solver=self.config["solver"],
          max_iter=self.config["max_iter"],
          class_weight="balanced",
          tol=self.config["tol"],
          random_state=self.config["random_state"],
          # Added these parameters to ensure sklearn changes won't affect us.
          # Should a sklearn update the defaults, we won't be affected.
          dual=False,
          fit_intercept=True,
          intercept_scaling=1,
          multi_class="auto",
          verbose=0,
          warm_start=False,
          n_jobs=None,
          l1_ratio=None,
      )
  
      # We need to use these later when saving the trained component.
      self._model_storage = model_storage
      self._resource = resource
  
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 4 to create a new LogisticRegressionClassifier object from inherited base classes: IntentClassifier, GraphComponent with example: obj = LogisticRegressionClassifier(config, name, model_storage, resource)