autoprognosis.plugins.explainers package
- class ExplainerPlugin(feature_names: list = [])
Bases:
object- abstract explain(X: DataFrame) DataFrame
- abstract static name() str
- plot(importances: DataFrame, feature_names: list | None = None) None
- abstract static pretty_name() str
- static type() str
- class Explainers
Bases:
PluginLoader- add(name: str, cls: Type) PluginLoader
- get(name: str, *args: Any, **kwargs: Any) Any
- get_type(name: str) Type
- list() List[str]
- list_available() List[str]
- reload() PluginLoader
- types() List[Type]
Submodules
- autoprognosis.plugins.explainers.base module
- autoprognosis.plugins.explainers.plugin_invase module
- autoprognosis.plugins.explainers.plugin_kernel_shap module
- autoprognosis.plugins.explainers.plugin_lime module
- autoprognosis.plugins.explainers.plugin_risk_effect_size module
- autoprognosis.plugins.explainers.plugin_shap_permutation_sampler module
- autoprognosis.plugins.explainers.plugin_symbolic_pursuit module