class_docstr: Handles incoming messages with low NLU confidence.
class_docstr_tok: ["Handles","incoming","messages","with","low","NLU","confidence","."]
docstr: Constructs a new fallback classifier.
docstr_tok: ["Constructs","a","new","fallback","classifier","."]
code: def __init__(self, config: Dict[Text, Any]) -> None:
      """Constructs a new fallback classifier."""
      self.component_config = config
  
imports: from __future__ import annotations
  import copy
  import logging
  from typing import Any, List, Text, Dict, Type, Union, Tuple, Optional
  from rasa.engine.graph import GraphComponent, ExecutionContext
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.shared.constants import DEFAULT_NLU_FALLBACK_INTENT_NAME
  from rasa.core.constants import DEFAULT_NLU_FALLBACK_THRESHOLD, DEFAULT_NLU_FALLBACK_AMBIGUITY_THRESHOLD
  from rasa.nlu.classifiers.classifier import IntentClassifier
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.nlu.constants import INTENT, INTENT_NAME_KEY, INTENT_RANKING_KEY, PREDICTED_CONFIDENCE_KEY
label_desc: Use image node_id 3 to create a new FallbackClassifier object from inherited base classes: GraphComponent, IntentClassifier with example: obj = FallbackClassifier(config)