logml.model_search.common

Classes

`ModelEvaluationData`(name, params, loss_name)	Result of model training and evaluation
`ModelHpoStatus`(value)	Status of HPO for the model during model seection.
`ModelSelectionResult`(dataset_hash, ...)	Model selection result

class logml.model_search.common.ModelHpoStatus(value)

Bases: str, enum.Enum

Status of HPO for the model during model seection.

FAILED = 'failed'

SKIPPED = 'skipped'

ALL_TRIALS_FAILED = 'all_trials_failed'

SUCCESS = 'success'

class logml.model_search.common.ModelEvaluationData(name: str, params: dict, loss_name: str, fit_success: bool = False, mean_loss: Optional[float] = 10000000000.0, loss_rel: Optional[float] = - 1, raw_metrics: Optional[list] = None, mean_metrics: Optional[dict] = None, std_metrics: Optional[dict] = None, hpo_status: logml.model_search.common.ModelHpoStatus = ModelHpoStatus.SKIPPED, error: Optional[str] = None, selection_test: Optional[str] = None, pvalue: Optional[float] = 1.0, raw_loss: Optional[list] = None, raw_metrics_erros: Optional[dict] = None, raw_metrics_not_applicable: Optional[dict] = None)

Bases: object

Result of model training and evaluation

name: str

params: dict

loss_name: str

fit_success: bool = False

mean_loss: Optional[float] = 10000000000.0

loss_rel: Optional[float] = -1

raw_metrics: Optional[list] = None

mean_metrics: Optional[dict] = None

std_metrics: Optional[dict] = None

hpo_status: logml.model_search.common.ModelHpoStatus = 'skipped'

error: str = None

selection_test: Optional[str] = None

pvalue: Optional[float] = 1.0

raw_loss: Optional[list] = None

raw_metrics_erros: Optional[dict] = None

raw_metrics_not_applicable: Optional[dict] = None

class logml.model_search.common.ModelSelectionResult(dataset_hash: str, baseline_model: logml.model_search.common.ModelEvaluationData, dataset_filename: typing.Optional[str] = None, selected_models: typing.Optional[typing.List[logml.model_search.common.ModelEvaluationData]] = <factory>, not_selected_models: typing.Optional[typing.List[logml.model_search.common.ModelEvaluationData]] = <factory>)

Bases: object

Model selection result

dataset_hash: str

baseline_model: logml.model_search.common.ModelEvaluationData

dataset_filename: Optional[str] = None

selected_models: Optional[List[logml.model_search.common.ModelEvaluationData]]

not_selected_models: Optional[List[logml.model_search.common.ModelEvaluationData]]

static from_dict(data: dict): Create instance of the class from dictionary (loaded from json).