code: def get_model(PARAMS):
      '''Get model according to parameters'''
      model_dict = {
          'LinearRegression': LinearRegression(),
          'SVR': SVR(),
          'KNeighborsRegressor': KNeighborsRegressor(),
          'DecisionTreeRegressor': DecisionTreeRegressor()
      }
      if not model_dict.get(PARAMS['model_name']):
          LOG.exception('Not supported model!')
          exit(1)
      
      model = model_dict[PARAMS['model_name']]
      
      try:
          if PARAMS['model_name'] == 'SVR':
              model.kernel = PARAMS['svr_kernel']
          elif PARAMS['model_name'] == 'KNeighborsRegressor':
              model.weights = PARAMS['knr_weights']
      except Exception as exception:
          LOG.exception(exception)
          raise
      return modef get_model(PARAMS):
      '''Get model according to parameters'''
      model_dict = {
          'LinearRegression': LinearRegression(),
          'SVR': SVR(),
          'KNeighborsRegressor': KNeighborsRegressor(),
          'DecisionTreeRegressor': DecisionTreeRegressor()
      }
      if not model_dict.get(PARAMS['model_name']):
          LOG.exception('Not supported model!')
          exit(1)
      
      model = model_dict[PARAMS['model_name']]
      
      try:
          if PARAMS['model_name'] == 'SVR':
              model.kernel = PARAMS['svr_kernel']
          elif PARAMS['model_name'] == 'KNeighborsRegressor':
              model.weights = PARAMS['knr_weights']
      except Exception as exception:
          LOG.exception(exception)
          raise
      return model
docs: Get model according to parameters