Google Cloud Ai Platform V1 Client - Class ExplanationParameters (0.26.2)

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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

Namespace

Google \ Cloud \ AIPlatform \ V1

Methods

__construct

Constructor.

Parameters
Name	Description
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.
↳ examples	Google\Cloud\AIPlatform\V1\Examples Example-based explanations that returns the nearest neighbors from the provided dataset.
↳ 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.

Returns
Type	Description
Google\Cloud\AIPlatform\V1\SampledShapleyAttribution|null

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.

Parameter
Name	Description
var	Google\Cloud\AIPlatform\V1\SampledShapleyAttribution

Returns
Type	Description
$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

Returns
Type	Description
Google\Cloud\AIPlatform\V1\IntegratedGradientsAttribution|null

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

Parameter
Name	Description
var	Google\Cloud\AIPlatform\V1\IntegratedGradientsAttribution

Returns
Type	Description
$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.

Returns
Type	Description
Google\Cloud\AIPlatform\V1\XraiAttribution|null

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.

Parameter
Name	Description
var	Google\Cloud\AIPlatform\V1\XraiAttribution

Returns
Type	Description
$this

getExamples

Example-based explanations that returns the nearest neighbors from the provided dataset.

Returns
Type	Description
Google\Cloud\AIPlatform\V1\Examples|null

hasExamples

setExamples

Example-based explanations that returns the nearest neighbors from the provided dataset.

Parameter
Name	Description
var	Google\Cloud\AIPlatform\V1\Examples

Returns
Type	Description
$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.

Returns
Type	Description
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.

Parameter
Name	Description
var	int

Returns
Type	Description
$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).

Returns
Type	Description
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).

Parameter
Name	Description
var	Google\Protobuf\ListValue

Returns
Type	Description
$this

getMethod

Returns
Type	Description
string