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 most probable label.
  
  Return only the most likely label.
  
  :param X: bow of input text
  :return: tuple of first, the most probable label and second,
           its probability.
docstr_tok: ["Given","a","bow","vector","of","an","input","text",",","predict","most","probable","label",".","Return","only","the","most","likely","label",".",":","param","X",":","bow","of","input","text",":","return",":","tuple","of","first",",","the","most","probable","label","and","second",",","its","probability","."]
code: def predict(self, X: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
      """Given a bow vector of an input text, predict most probable label.
  
      Return only the most likely label.
  
      :param X: bow of input text
      :return: tuple of first, the most probable label and second,
               its probability.
      """
      pred_result = self.predict_prob(X)
      # sort the probabilities retrieving the indices of
      # the elements in sorted order
  
      sorted_indices = np.fliplr(np.argsort(pred_result, axis=1))
      return sorted_indices, pred_result[:, sorted_indices]
  
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 14 for calling the SklearnIntentClassifier obj's underlying member method code with example usage: obj.predict(X) and returns: sorted_indices,  pred_result