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ExplanationParameters(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Parameters to configure explaining for Model's predictions.
Attributes
Name | Description |
sampled_shapley_attribution |
google.cloud.aiplatform_v1beta1.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. |
integrated_gradients_attribution |
google.cloud.aiplatform_v1beta1.types.IntegratedGradientsAttribution
An attribution method that computes Aumann- hapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365 |
xrai_attribution |
google.cloud.aiplatform_v1beta1.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. |
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). |