class_docstr: Intent classifier using the sklearn framework.
class_docstr_tok: ["Intent","classifier","using","the","sklearn","framework","."]
docstr: Given a bow vector of an input text, predict the intent label.
  
  Return probabilities for all labels.
  
  :param X: bow of input text
  :return: vector of probabilities containing one entry for each label.
docstr_tok: ["Given","a","bow","vector","of","an","input","text",",","predict","the","intent","label",".","Return","probabilities","for","all","labels",".",":","param","X",":","bow","of","input","text",":","return",":","vector","of","probabilities","containing","one","entry","for","each","label","."]
code: def predict_prob(self, X: np.ndarray) -> np.ndarray:
      """Given a bow vector of an input text, predict the intent label.
  
      Return probabilities for all labels.
  
      :param X: bow of input text
      :return: vector of probabilities containing one entry for each label.
      """
      if self.clf is None:
          raise RasaException(
              "Sklearn intent classifier has not been initialised and trained."
          )
  
      return self.clf.predict_proba(X)
  
imports: from __future__ import annotations
  import logging
  from rasa.nlu.featurizers.dense_featurizer.dense_featurizer import DenseFeaturizer
  import typing
  import warnings
  from typing import Any, Dict, List, Optional, Text, Tuple, Type
  import numpy
  import rasa.shared.utils.io
  import rasa.utils.io
  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 DOCS_URL_TRAINING_DATA_NLU
  from rasa.nlu.classifiers import LABEL_RANKING_LENGTH
  from rasa.shared.exceptions import RasaException
  from rasa.shared.nlu.constants import TEXT
  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.utils.tensorflow.constants import FEATURIZERS
label_desc: Use image node_id 13 for calling the SklearnIntentClassifier obj's underlying member method code with example usage: obj.predict_prob(X) and returns: self