- 3.52.0 (latest)
- 3.50.0
- 3.49.0
- 3.48.0
- 3.47.0
- 3.46.0
- 3.45.0
- 3.44.0
- 3.43.0
- 3.42.0
- 3.41.0
- 3.40.0
- 3.38.0
- 3.37.0
- 3.36.0
- 3.35.0
- 3.34.0
- 3.33.0
- 3.32.0
- 3.31.0
- 3.30.0
- 3.29.0
- 3.28.0
- 3.25.0
- 3.24.0
- 3.23.0
- 3.22.0
- 3.21.0
- 3.20.0
- 3.19.0
- 3.18.0
- 3.17.0
- 3.16.0
- 3.15.0
- 3.14.0
- 3.13.0
- 3.12.0
- 3.11.0
- 3.10.0
- 3.9.0
- 3.8.0
- 3.7.0
- 3.6.0
- 3.5.0
- 3.4.2
- 3.3.0
- 3.2.0
- 3.0.0
- 2.9.8
- 2.8.9
- 2.7.4
- 2.5.3
- 2.4.0
public interface ExplanationParametersOrBuilder extends MessageOrBuilderImplements
MessageOrBuilderMethods
getIntegratedGradientsAttribution()
public abstract IntegratedGradientsAttribution getIntegratedGradientsAttribution()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
.google.cloud.aiplatform.v1.IntegratedGradientsAttribution integrated_gradients_attribution = 2;
| Type | Description |
| IntegratedGradientsAttribution | The integratedGradientsAttribution. |
getIntegratedGradientsAttributionOrBuilder()
public abstract IntegratedGradientsAttributionOrBuilder getIntegratedGradientsAttributionOrBuilder()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
.google.cloud.aiplatform.v1.IntegratedGradientsAttribution integrated_gradients_attribution = 2;
| Type | Description |
| IntegratedGradientsAttributionOrBuilder |
getMethodCase()
public abstract ExplanationParameters.MethodCase getMethodCase()| Type | Description |
| ExplanationParameters.MethodCase |
getOutputIndices()
public abstract ListValue getOutputIndices()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).
.google.protobuf.ListValue output_indices = 5;
| Type | Description |
| ListValue | The outputIndices. |
getOutputIndicesOrBuilder()
public abstract ListValueOrBuilder getOutputIndicesOrBuilder()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).
.google.protobuf.ListValue output_indices = 5;
| Type | Description |
| ListValueOrBuilder |
getSampledShapleyAttribution()
public abstract SampledShapleyAttribution getSampledShapleyAttribution()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.
.google.cloud.aiplatform.v1.SampledShapleyAttribution sampled_shapley_attribution = 1;
| Type | Description |
| SampledShapleyAttribution | The sampledShapleyAttribution. |
getSampledShapleyAttributionOrBuilder()
public abstract SampledShapleyAttributionOrBuilder getSampledShapleyAttributionOrBuilder()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.
.google.cloud.aiplatform.v1.SampledShapleyAttribution sampled_shapley_attribution = 1;
| Type | Description |
| SampledShapleyAttributionOrBuilder |
getTopK()
public abstract int getTopK()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.
int32 top_k = 4;
| Type | Description |
| int | The topK. |
getXraiAttribution()
public abstract XraiAttribution getXraiAttribution()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.
.google.cloud.aiplatform.v1.XraiAttribution xrai_attribution = 3;
| Type | Description |
| XraiAttribution | The xraiAttribution. |
getXraiAttributionOrBuilder()
public abstract XraiAttributionOrBuilder getXraiAttributionOrBuilder()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.
.google.cloud.aiplatform.v1.XraiAttribution xrai_attribution = 3;
| Type | Description |
| XraiAttributionOrBuilder |
hasIntegratedGradientsAttribution()
public abstract boolean hasIntegratedGradientsAttribution()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
.google.cloud.aiplatform.v1.IntegratedGradientsAttribution integrated_gradients_attribution = 2;
| Type | Description |
| boolean | Whether the integratedGradientsAttribution field is set. |
hasOutputIndices()
public abstract boolean hasOutputIndices()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).
.google.protobuf.ListValue output_indices = 5;
| Type | Description |
| boolean | Whether the outputIndices field is set. |
hasSampledShapleyAttribution()
public abstract boolean hasSampledShapleyAttribution()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.
.google.cloud.aiplatform.v1.SampledShapleyAttribution sampled_shapley_attribution = 1;
| Type | Description |
| boolean | Whether the sampledShapleyAttribution field is set. |
hasXraiAttribution()
public abstract boolean hasXraiAttribution()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.
.google.cloud.aiplatform.v1.XraiAttribution xrai_attribution = 3;
| Type | Description |
| boolean | Whether the xraiAttribution field is set. |