class_docstr: Intent classifier using the Logistic Regression.
docstr: Persist this model into the passed directory.
docstr_tok: ["Persist","this","model","into","the","passed","directory","."]
code: def persist(self) -> None:
      """Persist this model into the passed directory."""
      with self._model_storage.write_to(self._resource) as model_dir:
          path = model_dir / f"{self._resource.name}.joblib"
          joblib.dump(self.clf, path)
          logger.debug(f"Saved intent classifier to '{path}'.")
  
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 10 for calling the LogisticRegressionClassifier obj's underlying member method code with example usage: obj.persist() without return types