public sealed class ExplanationParameters : IMessage<ExplanationParameters>, IEquatable<ExplanationParameters>, IDeepCloneable<ExplanationParameters>, IBufferMessage, IMessageReference documentation and code samples for the Cloud AI Platform v1beta1 API class ExplanationParameters.
Parameters to configure explaining for Model's predictions.
Implements
IMessageExplanationParameters, IEquatableExplanationParameters, IDeepCloneableExplanationParameters, IBufferMessage, IMessageNamespace
Google.Cloud.AIPlatform.V1Beta1Assembly
Google.Cloud.AIPlatform.V1Beta1.dll
Constructors
ExplanationParameters()
public ExplanationParameters()ExplanationParameters(ExplanationParameters)
public ExplanationParameters(ExplanationParameters other)| Parameter | |
|---|---|
| Name | Description |
other |
ExplanationParameters |
Properties
Examples
public Examples Examples { get; set; }Example-based explanations that returns the nearest neighbors from the provided dataset.
| Property Value | |
|---|---|
| Type | Description |
Examples |
|
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 |
ExplanationParametersMethodOneofCase |
|
OutputIndices
public ListValue OutputIndices { get; set; }If populated, only returns attributions that have [output_index][google.cloud.aiplatform.v1beta1.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.v1beta1.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 |
int |
|
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 |
|