class_docstr: TPOT estimator for regression problems.
class_docstr_tok: ["TPOT","estimator","for","regression","problems","."]
docstr: Set the sample of data used to verify pipelines work with the passed data set.
  
          
docstr_tok: ["Set","the","sample","of","data","used","to","verify","pipelines","work","with","the","passed","data","set","."]
code: def _init_pretest(self, features, target):
      """Set the sample of data used to verify pipelines work with the passed data set."""
      self.pretest_X, _, self.pretest_y, _ = train_test_split(
          features,
          target,
          random_state=self.random_state,
          test_size=None,
          train_size=min(50, int(0.9 * features.shape[0])),
      )
  
file_path: tpot/tpot/tpot.py
imports: from sklearn.model_selection import train_test_split
  from sklearn.utils import _safe_indexing
  import numpy
  from .base import TPOTBase
  from .config.classifier import classifier_config_dict
  from .config.regressor import regressor_config_dict
label_desc: Use image node_id 1 for calling the TPOTRegressor obj's underlying member method code with example usage: obj._init_pretest(features, target) without return types