tabensemb.data.dataderiver.RelativeDeriver#

class tabensemb.data.dataderiver.RelativeDeriver(**kwargs)[source]#

Bases: AbstractDeriver

Dividing a feature by another to derive a new feature. Required arguments are:

absolute_col: str: The feature that needs to be divided.
relative2_col: str: The feature that acts as the denominator.

Methods

__init__(**kwargs)#

The base class for all data-derivers, which will derive new features based on the input DataFrame and return the derived values, or load and return multimodal data. It is recommended to learn the derivation on the training set only.

Parameters:

kwargs: Arguments required by the deriver. It will be stored as self.kwargs.

`_defaults`()	Defaults values for arguments defined in `_cls_required_kwargs()` and `_required_kwargs()`
`_derive`(df, datamodule)	The main function for a data-deriver.
`_required_cols`()	Required column names in the tabular dataset by the data-deriver.
`_required_kwargs`()	kwargs required by the class.