docstr: Returns the arguments that need to passed in setup function for the experiment
docstr_tok: ["Returns","the","arguments","that","need","to","passed","in","setup","function","for","the","experiment"]
code: def _get_experiment_setup_kwargs(self, args: Dict, target: str):
      """Returns the arguments that need to passed in setup function for the experiment"""
      model_type = args["model_type"]
      # copy setup kwargs
      kwargs = self._select_keys(args, "setup_")
      # return kwargs
      if (
          model_type == "classification"
          or model_type == "regression"
          or model_type == "time_series"
      ):
          return {**kwargs, "target": target}
      elif model_type == "clustering" or model_type == "anomaly":
          return {**kwargs}
      raise Exception(f"Unrecognized model type '{model_type}'")
  
file_path: mindsdb/mindsdb/integrations/handlers/pycaret_handler/pycaret_handler.py
imports: from typing import Optional, Dict
  import os
  import pandas
  from mindsdb.integrations.libs.base import BaseMLEngine
  from pycaret.classification import ClassificationExperiment
  from pycaret.regression import RegressionExperiment
  from pycaret.time_series import TSForecastingExperiment
  from pycaret.clustering import ClusteringExperiment
  from pycaret.anomaly import AnomalyExperiment
label_desc: Use image node_id 5 for calling the PyCaretHandler obj's underlying member method code with example usage: obj._get_experiment_setup_kwargs(args, target) and returns: dict, dict