ezmsg.learn.process.adaptive_linear_regressor#

Adaptive linear regressor processor.

Note

This module supports the Array API standard via array_api_compat.get_namespace(). NaN checks and axis permutations use Array API operations; a NumPy boundary is applied before sklearn partial_fit/predict and before river learn_many/predict_many.

Classes

class AdaptiveLinearRegressorSettings(model_type=AdaptiveLinearRegressor.LINEAR, settings_path=None, model_kwargs=<factory>)[source]#

Bases: Settings

Parameters:
model_type: AdaptiveLinearRegressor = 'linear'#
settings_path: str | None = None#
model_kwargs: dict#
__init__(model_type=AdaptiveLinearRegressor.LINEAR, settings_path=None, model_kwargs=<factory>)#
Parameters:
Return type:

None

class AdaptiveLinearRegressorState[source]#

Bases: object

template: AxisArray | None = None#
model: GLM | RegressorMixin | None = None#
class AdaptiveLinearRegressorTransformer(*args, **kwargs)[source]#

Bases: BaseAdaptiveTransformer[AdaptiveLinearRegressorSettings, AxisArray, AxisArray, AdaptiveLinearRegressorState]

__init__(*args, **kwargs)[source]#
partial_fit(message)[source]#
Return type:

None

Parameters:

message (AxisArray)

class AdaptiveLinearRegressorUnit(*args, settings=None, **kwargs)[source]#

Bases: BaseAdaptiveTransformerUnit[AdaptiveLinearRegressorSettings, AxisArray, AxisArray, AdaptiveLinearRegressorTransformer]

Parameters:

settings (Settings | None)

SETTINGS#

alias of AdaptiveLinearRegressorSettings