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public sealed class ExplanationParameters : IMessage<ExplanationParameters>, IEquatable<ExplanationParameters>, IDeepCloneable<ExplanationParameters>, IBufferMessage, IMessage
Reference documentation and code samples for the Cloud AI Platform v1 API class ExplanationParameters.
Parameters to configure explaining for Model's predictions.
Implements
IMessage<ExplanationParameters>, IEquatable<ExplanationParameters>, IDeepCloneable<ExplanationParameters>, IBufferMessage, IMessageNamespace
Google.Cloud.AIPlatform.V1Assembly
Google.Cloud.AIPlatform.V1.dll
Constructors
ExplanationParameters()
public ExplanationParameters()
ExplanationParameters(ExplanationParameters)
public ExplanationParameters(ExplanationParameters other)
Parameter | |
---|---|
Name | Description |
other | ExplanationParameters |
Properties
IntegratedGradientsAttribution
public IntegratedGradientsAttribution IntegratedGradientsAttribution { get; set; }
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
Property Value | |
---|---|
Type | Description |
IntegratedGradientsAttribution |
MethodCase
public ExplanationParameters.MethodOneofCase MethodCase { get; }
Property Value | |
---|---|
Type | Description |
ExplanationParameters.MethodOneofCase |
OutputIndices
public ListValue OutputIndices { get; set; }
If populated, only returns attributions that have [output_index][google.cloud.aiplatform.v1.Attribution.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][google.cloud.aiplatform.v1.ExplanationParameters.top_k] indices of outputs. If neither top_k nor output_indices 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).
Property Value | |
---|---|
Type | Description |
ListValue |
SampledShapleyAttribution
public SampledShapleyAttribution SampledShapleyAttribution { get; set; }
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.
Property Value | |
---|---|
Type | Description |
SampledShapleyAttribution |
TopK
public int TopK { get; set; }
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.
Property Value | |
---|---|
Type | Description |
Int32 |
XraiAttribution
public XraiAttribution XraiAttribution { get; set; }
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.
Property Value | |
---|---|
Type | Description |
XraiAttribution |