class_docstr: Intent classifier which uses a Logistic Regression underneath
class_docstr_tok: ["Intent","classifier","which","uses","a","Logistic","Regression","underneath"]
docstr: The LogReg intent classifier can be configured by passing a
  :class:`.LogRegIntentClassifierConfig`
docstr_tok: ["The","LogReg","intent","classifier","can","be","configured","by","passing","a",":","class",":","`",".LogRegIntentClassifierConfig","`"]
code: def __init__(self, config=None, **shared):
      """The LogReg intent classifier can be configured by passing a
      :class:`.LogRegIntentClassifierConfig`"""
      super(LogRegIntentClassifier, self).__init__(config, **shared)
      self.classifier = None
      self.intent_list = None
      self.featurizer = None
  
imports: from __future__ import unicode_literals
  import json
  import logging
  from builtins import range, str, zip
  from pathlib import Path
  from snips_nlu.common.log_utils import DifferedLoggingMessage, log_elapsed_time
  from snips_nlu.common.utils import check_persisted_path, fitted_required, json_string
  from snips_nlu.constants import LANGUAGE, RES_PROBA
  from snips_nlu.dataset import validate_and_format_dataset
  from snips_nlu.exceptions import LoadingError, _EmptyDatasetUtterancesError
  from snips_nlu.intent_classifier.featurizer import Featurizer
  from snips_nlu.intent_classifier.intent_classifier import IntentClassifier
  from snips_nlu.intent_classifier.log_reg_classifier_utils import build_training_data, get_regularization_factor, text_to_utterance
  from snips_nlu.pipeline.configs import LogRegIntentClassifierConfig
  from snips_nlu.result import intent_classification_result
label_desc: Use image node_id 1 to create a new LogRegIntentClassifier object from inherited base classes: IntentClassifier with example: obj = LogRegIntentClassifier(config)