Note

This page is a reference documentation. It only explains the class signature, and not how to use it. Please refer to the What you really need to know section for the big picture.

julearn.pipeline.pipeline_creator.Step#

class julearn.pipeline.pipeline_creator.Step(name, estimator, apply_to=<factory>, needed_types=None, params_to_tune=None, row_select_col_type=None, row_select_vals=None)#

Step class.

This class represents a step in a pipeline.

Parameters:
namestr

The name of the step.

estimatorAny

The estimator to use.

apply_toColumnTypesLike

The types to apply this step to, by default “continuous”

needed_typesAny, optional

The types needed by this step (default is None)

row_select_col_typestr or list of str or set of str or ColumnTypes

The column types needed to select rows (default is None)

row_select_valsstr, int, bool or list of str, int, bool

The value(s) which should be selected in the row_select_col_type to select the rows used for training (default is None)

params_to_tuneOptional[Dict], optional

The parameters to tune for this step, by default None

__init__(name, estimator, apply_to=<factory>, needed_types=None, params_to_tune=None, row_select_col_type=None, row_select_vals=None)#
name: str#
estimator: Union[JuEstimatorLike, EstimatorLikeFit1, EstimatorLikeFit2, EstimatorLikeFity]#
apply_to: ColumnTypes#
needed_types: Optional[Union[List[str], Set[str], str, ColumnTypes]] = None#
params_to_tune: Optional[Dict] = None#
row_select_col_type: Optional[Union[List[str], Set[str], str, ColumnTypes]] = None#
row_select_vals: Optional[Union[str, int, list, bool]] = None#