class_docstr: Summarize given model performance on the train and test datasets based on selected scorers.
  
  Parameters
  ----------
  scorers: Union[Mapping[str, Union[str, Callable]], List[str]], default: None
      Scorers to override the default scorers, find more about the supported formats at
      https://docs.deepchecks.com/stable/user-guide/general/metrics_guide.html
  n_samples : int , default: 1_000_000
      number of samples to use for this check.
  random_state : int, default: 42
      random seed for all check internals.
class_docstr_tok: ["Summarize","given","model","performance","on","the","train","and","test","datasets","based","on","selected","scorers",".","Parameters","--","--","--","--","--","scorers",":","Union","[","Mapping","[","str",",","Union","[","str",",","Callable","]","]",",","List","[","str","]","]",",","default",":","None","Scorers","to","override","the","default","scorers",",","find","more","about","the","supported","formats","at","https",":","\/\/docs.deepchecks.com\/stable\/user-guide\/general\/metrics_guide.html","n_samples",":","int",",","default",":","1_000_000","number","of","samples","to","use","for","this","check",".","random_state",":","int",",","default",":","42","random","seed","for","all","check","internals","."]
code: def __init__(
      self,
      scorers: Optional[
          Union[Mapping[str, Union[str, Callable]], List[str]]
      ] = None,
      n_samples: int = 1_000_000,
      random_state: int = 42,
      **kwargs,
  ):
      super().__init__(**kwargs)
      self.scorers = scorers
      self.n_samples = n_samples
      self.random_state = random_state
  
file_path: deepchecks/deepchecks/tabular/checks/model_evaluation/single_dataset_performance.py
imports: from numbers import Number
  from typing import TYPE_CHECKING, Callable, Dict, List, Mapping, Optional, TypeVar, Union, cast
  import pandas
  from deepchecks.core import CheckResult, ConditionCategory, ConditionResult
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.core.reduce_classes import ReduceMetricClassMixin
  from deepchecks.tabular import Context
  from deepchecks.tabular.base_checks import SingleDatasetCheck
  from deepchecks.tabular.utils.task_type import TaskType
  from deepchecks.utils.docref import doclink
  from deepchecks.utils.strings import format_number
label_desc: Use image node_id 1 to create a new SingleDatasetPerformance object from inherited base classes: SingleDatasetCheck, ReduceMetricClassMixin with example: obj = SingleDatasetPerformance(scorers, n_samples, random_state)