GenericUnivariateSelect

Converter

DashAI.back.converters.scikit_learn.GenericUnivariateSelect

---

Select features using a configurable univariate statistical test and mode.

Supports multiple selection modes: k_best, percentile, fpr, fdr, and fwe. The scoring function and mode are configurable. Supervised: requires y at fit time.

Wraps scikit-learn's GenericUnivariateSelect.

Parameters

mode : string, default=percentile

Select features according to a percentile of the highest scores.

param, default=1e-05

Parameter of the mode.

Methods

fit(self, x: 'DashAIDataset', y: Optional[ForwardRef('DashAIDataset')] = None) -> 'FeatureSelectionConverter'

Defined on FeatureSelectionConverter

Fit the selector while remembering the input column types.

Parameters

x : DashAIDataset

The input dataset to fit the selector on.

y : DashAIDataset, optional

Target values for the supervised selectors. Defaults to None.

Returns

FeatureSelectionConverter

The fitted selector instance (self).

get_metadata(cls) -> 'Dict[str, Any]'

Defined on BaseConverter

Get metadata for the converter, used by the DashAI frontend.

Parameters

cls : type

The converter class (injected automatically by Python for classmethods).

Returns

Dict[str, Any]

Dictionary containing display name, short description, image preview path, category, icon, color, and whether the converter is supervised.

get_output_type(self, column_name: str = None) -> DashAI.back.types.dashai_data_type.DashAIDataType

Defined on FeatureSelectionConverter

Return the original DashAI data type of a retained column.

Parameters

column_name : str, optional

The name of the retained column. Defaults to None.

Returns

DashAIDataType

The original type of the column. Falls back to float64 when the input type is unknown (feature selectors only operate on numbers).

get_schema(cls) -> dict

Defined on ConfigObject

Generates the component related Json Schema.

Returns

dict

Dictionary representing the Json Schema of the component.

transform(self, x: 'DashAIDataset', y: Optional[ForwardRef('DashAIDataset')] = None) -> 'DashAIDataset'

Defined on SklearnWrapper

Transform the data using the fitted scikit-learn transformer.

Parameters

x : DashAIDataset

The input dataset to transform.

y : DashAIDataset, optional

Not used. Present for API consistency. Defaults to None.

Returns

DashAIDataset

The transformed dataset with updated DashAI column types.

validate_and_transform(self, raw_data: dict) -> dict

Defined on ConfigObject

It takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.

Parameters

raw_data : dict

A dictionary with the data provided by the user to initialize the model.

Returns

dict

A validated dictionary with the necessary objects.