ezmsg.learn.process.sgd#

Classes

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

Bases: BaseAdaptiveTransformerUnit[SGDDecoderSettings, AxisArray, ClassifierMessage, SGDDecoderTransformer]

Parameters:: settings (Settings | None)

SETTINGS#: alias of SGDDecoderSettings

class SGDDecoderSettings(alpha=1e-05, eta0=0.0003, loss='hinge', label_weights=None, settings_path=None)[source]#

Bases: Settings

Parameters:

alpha (float)
eta0 (float)
loss (str)
label_weights (dict[str, float] | None)
settings_path (str | None)

alpha: float = 1e-05#

eta0: float = 0.0003#

loss: str = 'hinge'#

label_weights: dict[str, float] | None = None#

settings_path: str | None = None#

__init__(alpha=1e-05, eta0=0.0003, loss='hinge', label_weights=None, settings_path=None)#

Parameters:

alpha (float)
eta0 (float)
loss (str)
label_weights (dict[str, float] | None)
settings_path (str | None)

Return type:

None

class SGDDecoderState[source]#

Bases: object

model: Any = None#

b_first_train: bool = True#

class SGDDecoderTransformer(*args, **kwargs)[source]#

Bases: BaseAdaptiveTransformer[SGDDecoderSettings, AxisArray, ClassifierMessage, SGDDecoderState]

SGD-based online classifier.

Online Passive-Aggressive Algorithms <http://jmlr.csail.mit.edu/papers/volume7/crammer06a/crammer06a.pdf> K. Crammer, O. Dekel, J. Keshat, S. Shalev-Shwartz, Y. Singer - JMLR (2006)

partial_fit(message)[source]#

Return type:: None
Parameters:: message (AxisArray)