docstr: Return the following statistics of the training result:
  
  - dataset name
  - metric used
  - best validation score
  - number of target algorithm runs
  - number of successful target algorithm runs
  - number of crashed target algorithm runs
  - number of target algorithm runs that exceeded the memory limit
  - number of target algorithm runs that exceeded the time limit
  
  Returns
  -------
  str
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code: def sprint_statistics(self):
      """Return the following statistics of the training result:
  
      - dataset name
      - metric used
      - best validation score
      - number of target algorithm runs
      - number of successful target algorithm runs
      - number of crashed target algorithm runs
      - number of target algorithm runs that exceeded the memory limit
      - number of target algorithm runs that exceeded the time limit
  
      Returns
      -------
      str
      """
      return self.automl_.sprint_statistics()
  
imports: from __future__ import annotations
  from typing import Any, Dict, Iterable, List, Mapping, Optional, Sequence, Tuple, Type, Union
  import warnings
  import dask.distributed
  import joblib
  import numpy
  import pandas
  from ConfigSpace.configuration_space import Configuration, ConfigurationSpace
  from scipy.sparse import spmatrix
  from sklearn.base import BaseEstimator, ClassifierMixin, RegressorMixin
  from sklearn.ensemble import VotingClassifier, VotingRegressor
  from sklearn.utils.multiclass import type_of_target
  from smac.runhistory.runhistory import RunInfo, RunValue
  from typing_extensions import Literal
  from autosklearn.automl import AutoML, AutoMLClassifier, AutoMLRegressor
  from autosklearn.data.validation import SUPPORTED_FEAT_TYPES, SUPPORTED_TARGET_TYPES, convert_if_sparse
  from autosklearn.ensembles.abstract_ensemble import AbstractEnsemble
  from autosklearn.ensembles.ensemble_selection import EnsembleSelection
  from autosklearn.ensembles.multiobjective_dummy_ensemble import MultiObjectiveDummyEnsemble
  from autosklearn.metrics import Scorer
  from autosklearn.pipeline.base import BasePipeline
  from autosklearn.util.smac_wrap import SMACCallback
label_desc: Use image node_id 18 for calling the AutoSklearnEstimator obj's underlying member method code with example usage: obj.sprint_statistics() and returns: self