ezmsg.learn.util#

Functions

get_regressor(regressor_type, regressor_name)[source]#
Parameters:

Classes

class AdaptiveLinearRegressor(*values)[source]#

Bases: str, Enum

LINEAR = 'linear'#
LOGISTIC = 'logistic'#
SGD = 'sgd'#
PAR = 'par'#
class ClassifierMessage(data, dims, axes=<factory>, attrs=<factory>, key='', labels=<factory>)[source]#

Bases: AxisArray

Parameters:
labels: list[str]#
__init__(data, dims, axes=<factory>, attrs=<factory>, key='', labels=<factory>)#
Parameters:
Return type:

None

axes: typing.Dict[str, AxisBase]#
attrs: typing.Dict[str, typing.Any]#
data: npt.NDArray#
dims: typing.List[str]#
class RegressorType(*values)[source]#

Bases: str, Enum

ADAPTIVE = 'adaptive'#
STATIC = 'static'#
class StaticLinearRegressor(*values)[source]#

Bases: str, Enum

LINEAR = 'linear'#
RIDGE = 'ridge'#
class RegressorType(*values)[source]#

Bases: str, Enum

ADAPTIVE = 'adaptive'#
STATIC = 'static'#
class AdaptiveLinearRegressor(*values)[source]#

Bases: str, Enum

LINEAR = 'linear'#
LOGISTIC = 'logistic'#
SGD = 'sgd'#
PAR = 'par'#
class StaticLinearRegressor(*values)[source]#

Bases: str, Enum

LINEAR = 'linear'#
RIDGE = 'ridge'#
get_regressor(regressor_type, regressor_name)[source]#
Parameters:
class ClassifierMessage(data, dims, axes=<factory>, attrs=<factory>, key='', labels=<factory>)[source]#

Bases: AxisArray

Parameters:
labels: list[str]#
__init__(data, dims, axes=<factory>, attrs=<factory>, key='', labels=<factory>)#
Parameters:
Return type:

None