hyperimpute.plugins.imputers.base module

class ImputerPlugin(random_state: int = 0)

Bases: _BaseImputer, Plugin

Base class for the imputation plugins.

It provides the implementation for plugin.Plugin.type() static method.

Each derived class must implement the following methods(inherited from plugin.Plugin):

name() - a static method that returns the name of the plugin. e.g., EM, mice, etc. hyperparameter_space() - a static method that returns the hyperparameters that can be tuned during the optimization. The method will return a list of Params derived objects. _fit() - internal implementation, called by the fit() method. _transform() - internal implementation, called by the transform() method.

If any method implementation is missing, the class constructor will fail.

_abc_impl = <_abc_data object>

_predict(X: DataFrame, *args: Any, **kwargs: Any) → DataFrame

_predict_proba(X: DataFrame) → DataFrame

module_relative_path: Optional[Path]

static subtype() → str

static type() → str