docstr: Fit method for clustering task
  
  :param train_data: data used for model training
docstr_tok: ["Fit","method","for","clustering","task",":","param","train_data",":","data","used","for","model","training"]
code: def fit(self, train_data: InputData):
      """
      Fit method for clustering task
  
      :param train_data: data used for model training
      """
  
      warnings.filterwarnings("ignore", category=RuntimeWarning)
      operation_implementation = self.operation_impl(
          **self.params_for_fit.to_dict()
      )
      with ImplementationRandomStateHandler(
          implementation=operation_implementation
      ):
          operation_implementation.fit(train_data.features)
      return operation_implementation
  
file_path: FEDOT/fedot/core/operations/evaluation/clustering.py
imports: import warnings
  from typing import Optional
  from sklearn.cluster import KMeans
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.evaluation.evaluation_interfaces import SkLearnEvaluationStrategy
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.utilities.random import ImplementationRandomStateHandler
label_desc: Use image node_id 2 for calling the SkLearnClusteringStrategy obj's underlying member method code with example usage: obj.fit(train_data) and returns: operation_implementation