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Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class ExplanationParameters.
Parameters to configure explaining for Model's predictions.
Generated from protobuf message google.cloud.aiplatform.v1.ExplanationParameters
Methods
__construct
Constructor.
data
array
Optional. Data for populating the Message object.
↳ sampled_shapley_attribution
Google\Cloud\AIPlatform\V1\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\V1\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
↳ xrai_attribution
Google\Cloud\AIPlatform\V1\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\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_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).
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 .
Generated from protobuf field .google.cloud.aiplatform.v1.SampledShapleyAttribution sampled_shapley_attribution = 1;
hasSampledShapleyAttribution
setSampledShapleyAttribution
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 .
Generated from protobuf field .google.cloud.aiplatform.v1.SampledShapleyAttribution sampled_shapley_attribution = 1;
$this
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
Generated from protobuf field .google.cloud.aiplatform.v1.IntegratedGradientsAttribution integrated_gradients_attribution = 2;
hasIntegratedGradientsAttribution
setIntegratedGradientsAttribution
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
Generated from protobuf field .google.cloud.aiplatform.v1.IntegratedGradientsAttribution integrated_gradients_attribution = 2;
$this
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.
Generated from protobuf field .google.cloud.aiplatform.v1.XraiAttribution xrai_attribution = 3;
hasXraiAttribution
setXraiAttribution
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.
Generated from protobuf field .google.cloud.aiplatform.v1.XraiAttribution xrai_attribution = 3;
$this
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.
Generated from protobuf field int32 top_k = 4;
int
setTopK
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.
Generated from protobuf field int32 top_k = 4;
var
int
$this
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_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).
Generated from protobuf field .google.protobuf.ListValue output_indices = 5;
Google\Protobuf\ListValue|null
hasOutputIndices
clearOutputIndices
setOutputIndices
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_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).
Generated from protobuf field .google.protobuf.ListValue output_indices = 5;
var
Google\Protobuf\ListValue
$this
getMethod
string
