Class ExplanationParameters (1.16.0)

Version 1.16.0

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ExplanationParameters(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Parameters to configure explaining for Model's predictions.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Attributes

Name	Description
sampled_shapley_attribution	google.cloud.aiplatform_v1.types.SampledShapleyAttribution An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265. This field is a member of `oneof`_ ``method``.
integrated_gradients_attribution	google.cloud.aiplatform_v1.types.IntegratedGradientsAttribution An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365 This field is a member of `oneof`_ ``method``.
xrai_attribution	google.cloud.aiplatform_v1.types.XraiAttribution An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead. This field is a member of `oneof`_ ``method``.
top_k	int If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.
output_indices	google.protobuf.struct_pb2.ListValue If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining. If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indeices is populated, returns the argmax index of the outputs. Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes).

Inheritance

builtins.object > proto.message.Message > ExplanationParameters