hyperparameter_hunter.data.data_chunks package

Submodules

hyperparameter_hunter.data.data_chunks.input_chunks module

class hyperparameter_hunter.data.data_chunks.input_chunks.BaseInputChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_core.BaseDataChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, \*args, \*\*kwargs)

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_end
on_run_start

class hyperparameter_hunter.data.data_chunks.input_chunks.TrainInputChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_chunks.input_chunks.BaseInputChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, \*args, \*\*kwargs)

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_end
on_run_start

class hyperparameter_hunter.data.data_chunks.input_chunks.OOFInputChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_chunks.input_chunks.BaseInputChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, \*args, \*\*kwargs)

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_end
on_run_start

class hyperparameter_hunter.data.data_chunks.input_chunks.HoldoutInputChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_chunks.input_chunks.BaseInputChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, \*args, \*\*kwargs)

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_end
on_run_start

class hyperparameter_hunter.data.data_chunks.input_chunks.TestInputChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_chunks.input_chunks.BaseInputChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, \*args, \*\*kwargs)

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_end
on_run_start

hyperparameter_hunter.data.data_chunks.prediction_chunks module

class hyperparameter_hunter.data.data_chunks.prediction_chunks.BasePredictionChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_core.BaseDataChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, \*args, \*\*kwargs)
on_run_end(self, prediction, …)	…

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_start

on_exp_start(self, *args, **kwargs)

on_rep_start(self, *args, **kwargs)

on_fold_start(self, *args, **kwargs)

on_run_end(self, prediction, feature_engineer, target_column, *args, **kwargs)

…

Parameters

prediction: Array-like

feature_engineer: FeatureEngineer

target_column: List[str]

*args: Tuple

**kwargs: Dict

on_fold_end(self, runs:int, *args, **kwargs)

on_rep_end(self, n_splits:int, *args, **kwargs)

on_exp_end(self, n_repeats:int)

class hyperparameter_hunter.data.data_chunks.prediction_chunks.OOFPredictionChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_chunks.prediction_chunks.BasePredictionChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, zero_predictions, \*args, …)
on_fold_end(self, validation_index, runs, …)
on_run_end(self, prediction, …)	…

on_exp_end
on_fold_start
on_rep_end
on_rep_start
on_run_start

on_exp_start(self, zero_predictions, *args, **kwargs)

on_rep_start(self, zero_predictions, *args, **kwargs)

on_fold_end(self, validation_index, runs:int, *args, **kwargs)

on_rep_end(self, *args, **kwargs)

class hyperparameter_hunter.data.data_chunks.prediction_chunks.HoldoutPredictionChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_chunks.prediction_chunks.BasePredictionChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, \*args, \*\*kwargs)
on_run_end(self, prediction, …)	…

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_start

class hyperparameter_hunter.data.data_chunks.prediction_chunks.TestPredictionChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_chunks.prediction_chunks.BasePredictionChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, \*args, \*\*kwargs)
on_run_end(self, prediction, …)	…

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_start

hyperparameter_hunter.data.data_chunks.target_chunks module

class hyperparameter_hunter.data.data_chunks.target_chunks.BaseTargetChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_core.BaseDataChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, \*args, \*\*kwargs)

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_end
on_run_start

class hyperparameter_hunter.data.data_chunks.target_chunks.TrainTargetChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_chunks.target_chunks.BaseTargetChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, \*args, \*\*kwargs)

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_end
on_run_start

class hyperparameter_hunter.data.data_chunks.target_chunks.OOFTargetChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_chunks.target_chunks.BaseTargetChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, empty_output_frame, …)
on_run_end(self, \*args, \*\*kwargs)

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_start

on_exp_start(self, empty_output_frame, *args, **kwargs)

on_rep_start(self, empty_output_frame, *args, **kwargs)

on_fold_start(self, *args, **kwargs)

on_run_start(self, *args, **kwargs)

on_run_end(self, *args, **kwargs)

on_fold_end(self, validation_index, *args, **kwargs)

on_rep_end(self, n_splits:int, *args, **kwargs)

on_exp_end(self, n_repeats:int, *args, **kwargs)

class hyperparameter_hunter.data.data_chunks.target_chunks.HoldoutTargetChunk(d: Optional[pandas.core.frame.DataFrame])

Bases: hyperparameter_hunter.data.data_chunks.target_chunks.BaseTargetChunk

Create logical separations between “columns” of data for a BaseDataset

Parameters

d: pd.DataFrame, or None

Raw data representing the initial state of the data to be handled by this chunk, and its transformed self (BaseDataChunk.T)

Attributes

T: _BaseDataChunk

Extra data chunk tracking transformations/inversions applied to _BaseDataChunk attributes via FeatureEngineer. If no feature engineering is performed, T can be ignored

Methods

on_exp_start(self, empty_output_frame, …)
on_run_end(self, \*args, \*\*kwargs)

on_exp_end
on_fold_end
on_fold_start
on_rep_end
on_rep_start
on_run_start

on_exp_start(self, empty_output_frame, *args, **kwargs)

on_rep_start(self, empty_output_frame, *args, **kwargs)

on_fold_start(self, *args, **kwargs)

on_run_start(self, *args, **kwargs)

on_run_end(self, *args, **kwargs)

on_fold_end(self, *args, **kwargs)

on_rep_end(self, n_splits:int, *args, **kwargs)

on_exp_end(self, n_repeats:int, *args, **kwargs)

Module contents