AdditiveChi2Sampler

Converter

DashAI.back.converters.scikit_learn.AdditiveChi2Sampler

---

Approximate the additive chi-squared kernel using Fourier sampling.

Maps features to a higher-dimensional space that approximates the additive chi-squared kernel, enabling efficient linear classification. Wraps scikit-learn's AdditiveChi2Sampler.

Parameters

sample_steps : integer, default=2

The number of sample steps (shuffling) to perform.

sample_interval, default=None

The number of samples generated between each original sample.

Methods

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

Defined on AdditiveChi2Sampler

Return the DashAI data type produced by this converter for a column.

Parameters

column_name : str, optional

Not used; all output columns share the same type. Defaults to None.

Returns

DashAIDataType

A Float type backed by pyarrow.float64().

changes_row_count(self) -> 'bool'

Defined on BaseConverter

Indicate whether this converter changes the number of dataset rows.

Returns

bool

True if the converter may add or remove rows, False otherwise.

fit(self, x: 'DashAIDataset', y: Optional[ForwardRef('DashAIDataset')] = None) -> DashAI.back.converters.base_converter.BaseConverter

Defined on SklearnWrapper

Fit the scikit-learn transformer to the data.

Parameters

x : DashAIDataset

The input dataset to fit the transformer on.

y : DashAIDataset, optional

Target values for supervised transformers. Defaults to None.

Returns

BaseConverter

The fitted transformer 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_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.