ezmsg.learn.util

Functions

get_regressor(regressor_type, regressor_name)

Parameters:

• regressor_type (RegressorType | str)

• regressor_name (AdaptiveLinearRegressor | StaticLinearRegressor | str)

Classes

class AdaptiveLinearRegressor(*values)

Bases: str, Enum

LINEAR = 'linear'

LOGISTIC = 'logistic'

SGD = 'sgd'

PAR = 'par'

class ClassifierMessage(data, dims, axes=<factory>, attrs=<factory>, key='', labels=<factory>)

Bases: AxisArray

Parameters:

• data (ndarray[tuple[Any, ...], dtype[_ScalarT]])

• dims (list[str])

• axes (dict[str, AxisBase])

• attrs (dict[str, Any])

• key (str)

• labels (list[str])

labels: list[str]

__init__(data, dims, axes=<factory>, attrs=<factory>, key='', labels=<factory>)

Parameters:

• data (ndarray[tuple[Any, ...], dtype[_ScalarT]])

• dims (list[str])

• axes (dict[str, AxisBase])

• attrs (dict[str, Any])

• key (str)

• labels (list[str])

Return type:

None

class RegressorType(*values)

Bases: str, Enum

ADAPTIVE = 'adaptive'

STATIC = 'static'

class StaticLinearRegressor(*values)

Bases: str, Enum

LINEAR = 'linear'

RIDGE = 'ridge'