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merlin.datasets.metadata module

class merlin.datasets.metadata.DatasetMetadata(name, description, features, num_instances, subset=None, num_features=None, normalization=None, task_type=<factory>, num_classes=None, characteristics=<factory>, homepage=None, license=None, citation=None, creators=<factory>, year=None, feature_relationships=None)

Bases: object

characteristics: list[str]
citation: Optional[str] = None
creators: list[str]
description: str
feature_relationships: Optional[str] = None
features: list[Feature]
classmethod from_dict(data)
Return type:

DatasetMetadata

homepage: Optional[str] = None
license: Optional[str] = None
name: str
normalization: Optional[Normalization] = None
num_classes: Optional[int] = None
num_features: int = None
num_instances: int
subset: str = None
task_type: Optional[list[str]]
to_dict()

Convert the metadata to a dictionary format

Return type:

dict[str, Any]

year: Optional[int] = None
class merlin.datasets.metadata.Feature(name, description, type, value_range=None, unit=None, stats=None, normalization=None)

Bases: object

description: str
name: str
normalization: Optional[FeatureNormalization] = None
stats: Optional[dict[str, float]] = None
to_text()
Return type:

str

type: str
unit: Optional[str] = None
value_range: Optional[tuple] = None
class merlin.datasets.metadata.FeatureNormalization(original_unit=None, scale_factor=None, offset=None)

Bases: object

offset: Optional[float] = None
original_unit: Optional[str] = None
scale_factor: Optional[float] = None
to_text()
Return type:

str

class merlin.datasets.metadata.Normalization(method, range, per_feature=True)

Bases: object

method: str
per_feature: bool = True
range: tuple
to_text()
Return type:

str