Cli Ml

class dffml.cli.ml.Accuracy(*args, **kwargs)

Assess model accuracy on data from given sources

CONFIG

alias of dffml.cli.ml.AccuracyCMDConfig

class dffml.cli.ml.AccuracyCMDConfig(model: dffml.model.model.Model, scorer: dffml.accuracy.accuracy.AccuracyScorer, features: dffml.feature.feature.Features = [], sources: dffml.source.source.Sources = <factory>)

no_enforce_immutable()

By default, all properties of a config object are immutable. If you would like to mutate immutable properties, you must explicitly call this method using it as a context manager.

Examples

>>> from dffml import config
>>>
>>> @config
... class MyConfig:
...     C: int
>>>
>>> config = MyConfig(C=2)
>>> with config.no_enforce_immutable():
...     config.C = 1

class dffml.cli.ml.MLCMD(*args, **kwargs)

Commands which use models share many similar arguments.

class dffml.cli.ml.MLCMDConfig(model: dffml.model.model.Model, sources: dffml.source.source.Sources = <factory>)

no_enforce_immutable()

By default, all properties of a config object are immutable. If you would like to mutate immutable properties, you must explicitly call this method using it as a context manager.

Examples

>>> from dffml import config
>>>
>>> @config
... class MyConfig:
...     C: int
>>>
>>> config = MyConfig(C=2)
>>> with config.no_enforce_immutable():
...     config.C = 1

class dffml.cli.ml.Predict(extra_config=None, **kwargs)

Evaluate features against records and produce a prediction

record

alias of dffml.cli.ml.PredictRecord

class dffml.cli.ml.PredictAll(*args, **kwargs)

Predicts for all sources

CONFIG

alias of dffml.cli.ml.PredictAllConfig

class dffml.cli.ml.PredictAllConfig(model: dffml.model.model.Model, sources: dffml.source.source.Sources = <factory>, update: bool = False, pretty: bool = False)

no_enforce_immutable()

By default, all properties of a config object are immutable. If you would like to mutate immutable properties, you must explicitly call this method using it as a context manager.

Examples

>>> from dffml import config
>>>
>>> @config
... class MyConfig:
...     C: int
>>>
>>> config = MyConfig(C=2)
>>> with config.no_enforce_immutable():
...     config.C = 1

class dffml.cli.ml.PredictRecord(*args, **kwargs)

Predictions for individual records

CONFIG

alias of dffml.cli.ml.PredictRecordConfig

class dffml.cli.ml.PredictRecordConfig(keys: List[str], model: dffml.model.model.Model, sources: dffml.source.source.Sources = <factory>, update: bool = False, pretty: bool = False)

no_enforce_immutable()

By default, all properties of a config object are immutable. If you would like to mutate immutable properties, you must explicitly call this method using it as a context manager.

Examples

>>> from dffml import config
>>>
>>> @config
... class MyConfig:
...     C: int
>>>
>>> config = MyConfig(C=2)
>>> with config.no_enforce_immutable():
...     config.C = 1

class dffml.cli.ml.Train(*args, **kwargs)

Train a model on data from given sources

CONFIG

alias of dffml.cli.ml.MLCMDConfig