arthurai.core.attributes.ArthurAttribute

class arthurai.core.attributes.ArthurAttribute(name, value_type, stage, id=None, label=None, position=None, categorical=False, min_range=None, max_range=None, monitor_for_bias=False, categories=None, bins=None, is_unique=False, is_positive_predicted_attribute=False, attribute_link=None, gt_class_link=None, token_attribute_link=None, implicit=False)

Bases: arthurai.core.base.ArthurBaseJsonDataclass

ArthurAttribute encapsulates data associated with a model attribute

Parameters

• attribute_link (Optional[str]) – Only applicable for GroundTruth or PredictedValue staged attributes. If stage is equal to GroundTruth, this represents the associated PredictedValue attribute and vice versa

• is_positive_predicted_attribute (bool) – Only applicable for PredictedValue attributes on a Binary Classification model. Should be set to True on the positive predicted value attribute.

• is_unique (bool) – Boolean value used to signal if the values of this attribute are unique. To set an attribute to be unique, use arthur_model.get(name=attribute_name).set(is_unique=True).

• bins (Optional[List[AttributeBin]]) – List of bin cut-offs used to discretize continuous attributes. Use None as an open ended value. [None, 18, 65, None] represents the three following bins: value < 18, 18 < value < 65, value > 65. To modify an attribute’s bins, use arthur_model.get_attribute(name=attribute_name).set(bins=[None, cutoff_1, ..., cutoff_n, None]).

• monitor_for_bias (bool) – boolean value set to True if the attribute should be monitored for bias. To modify an attributes’s bias monitoring status, use arthurai.core.models.ArthurModel.set_attribute_as_sensitive().

• max_range (Union[int, float, None]) – Max value for a continuous attribute. To modify an attribute’s range, use arthur_model.get(name=attribute_name).set(range=[min_value, max_value]).

• min_range (Union[int, float, None]) – Min value for a continuous attribute. To modify an attribute’s range, use arthur_model.get(name=attribute_name).set(range=[min_value, max_value]).

• categorical (Optional[bool]) – Boolean value set to True if the attribute has categorical values. To set an attribute to be categorical, use arthur_model.get_attribute(name=attribute_name).set(categorical=true).

• position (Optional[int]) – The array position of attribute within the stage. Required in the PREDICT_FUNCTION_INPUT stage.

• label (Optional[str]) – Label for attribute. If attribute has an encoded name, a more readable label can be set.

• stage (Stage) – arthurai.common.constants.Stage of this attribute in the model pipeline. To modify an attribute’s stage, use arthur_model.get(name=attribute_name).set(stage=stage_value). See arthurai.common.constants.Stage for the different stage values an attribute can have.

• value_type (ValueType) – arthurai.common.constants.ValueType associated with this attributes values. Non-modifiable.

• name (str) – Name of the attribute. Attribute names can only contain alpha-numeric characters and underscores and cannot start with a number. To modify an attribute’s name, use arthurai.core.models.ArthurModel.rename_attribute().

• categories (Optional[List[AttributeCategory]]) – [Only for Categorical Attributes] If the attribute is categorical, this will contain the attribute’s categorical values and the labels for each value. It is required only if the categorical flag is set to true. To modify the category values, use arthur_model.get(name=attribute_name).set([{'value': value_1}, ..., {'value': value_n}]). To mofidy the category labels, use arthurai.core.models.ArthurModel.set_attribute_labels().

• gt_class_link (Optional[str]) – Optional link for a predicted attribute to its corresponding value in a ground truth class attribute

• implicit (bool) – is the attribute implicitly created by the API

Methods

clean_nones	Helper function to filter out None objects from a json or dictionary representation of an object
from_dict	rtype TypeVar(A, bound= DataClassJsonMixin)
from_json	rtype TypeVar(A, bound= DataClassJsonMixin)
schema	rtype SchemaF[TypeVar(A)]
set	Set one or many of the available properties of the ArthurAttribute class
short_name
to_dict	Creates a dictionary representation of this object
to_json	Creates a json representation of this object

Attributes

attribute_link
bins
categorical
categories
dataclass_json_config
gt_class_link
id
implicit
is_positive_predicted_attribute
is_unique
label
max_range
min_range
monitor_for_bias
position
token_attribute_link
name
value_type
stage

static clean_nones(d)

Helper function to filter out None objects from a json or dictionary representation of an object

Parameters

d – a Dictionary or Json representation of an ArthurBaseJsonDataclass object

Returns

Dictionary of the object with all None components removed

set(**kwargs)

Set one or many of the available properties of the ArthurAttribute class

to_dict(skip_none=True)

Creates a dictionary representation of this object

This function can be applied to any extension of the ArthurBaseJsonDataClass

Return type

dict

Returns

Dictionary of object data

to_json(skip_none=True)

Creates a json representation of this object

This function can be applied to any extension of the ArthurBaseJsonDataClass

Return type

str

Returns

json of object data