Struct ModelEvaluation

#[non_exhaustive]
pub struct ModelEvaluation {
    pub name: String,
    pub display_name: String,
    pub metrics_schema_uri: String,
    pub metrics: Option<Value>,
    pub create_time: Option<Timestamp>,
    pub slice_dimensions: Vec<String>,
    pub data_item_schema_uri: String,
    pub annotation_schema_uri: String,
    pub model_explanation: Option<ModelExplanation>,
    pub explanation_specs: Vec<ModelEvaluationExplanationSpec>,
    pub metadata: Option<Value>,
    /* private fields */
}

A collection of metrics calculated by comparing Model’s predictions on all of the test data against annotations from the test data.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

name: String

Output only. The resource name of the ModelEvaluation.

display_name: String

The display name of the ModelEvaluation.

metrics_schema_uri: String

Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 Schema Object.

metrics: Option<Value>

Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri

create_time: Option<Timestamp>

Output only. Timestamp when this ModelEvaluation was created.

slice_dimensions: Vec<String>

All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = <dimension>.

data_item_schema_uri: String

Points to a YAML file stored on Google Cloud Storage describing [EvaluatedDataItemView.data_item_payload][] and EvaluatedAnnotation.data_item_payload. The schema is defined as an OpenAPI 3.0.2 Schema Object.

This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.

annotation_schema_uri: String

Points to a YAML file stored on Google Cloud Storage describing [EvaluatedDataItemView.predictions][], [EvaluatedDataItemView.ground_truths][], EvaluatedAnnotation.predictions, and EvaluatedAnnotation.ground_truths. The schema is defined as an OpenAPI 3.0.2 Schema Object.

This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.

model_explanation: Option<ModelExplanation>

Aggregated explanation metrics for the Model’s prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models.

explanation_specs: Vec<ModelEvaluationExplanationSpec>

Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

metadata: Option<Value>

The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of “pipeline_job_id”, “evaluation_dataset_type”, “evaluation_dataset_path”, “row_based_metrics_path”.

Implementations

impl ModelEvaluation

pub fn new() -> Self

pub fn set_name<T: Into<String>>(self, v: T) -> Self

Sets the value of name.

pub fn set_display_name<T: Into<String>>(self, v: T) -> Self

Sets the value of display_name.

pub fn set_metrics_schema_uri<T: Into<String>>(self, v: T) -> Self

Sets the value of metrics_schema_uri.

pub fn set_metrics<T: Into<Option<Value>>>(self, v: T) -> Self

Sets the value of metrics.

pub fn set_create_time<T: Into<Option<Timestamp>>>(self, v: T) -> Self

Sets the value of create_time.

pub fn set_slice_dimensions<T, V>(self, v: T) -> Self

where T: IntoIterator<Item = V>, V: Into<String>,

Sets the value of slice_dimensions.

pub fn set_data_item_schema_uri<T: Into<String>>(self, v: T) -> Self

Sets the value of data_item_schema_uri.

pub fn set_annotation_schema_uri<T: Into<String>>(self, v: T) -> Self

Sets the value of annotation_schema_uri.

pub fn set_model_explanation<T: Into<Option<ModelExplanation>>>( self, v: T, ) -> Self

Sets the value of model_explanation.

pub fn set_explanation_specs<T, V>(self, v: T) -> Self

where T: IntoIterator<Item = V>, V: Into<ModelEvaluationExplanationSpec>,

Sets the value of explanation_specs.

pub fn set_metadata<T: Into<Option<Value>>>(self, v: T) -> Self

Sets the value of metadata.

Trait Implementations

impl Clone for ModelEvaluation

fn clone(&self) -> ModelEvaluation

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ModelEvaluation

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for ModelEvaluation

fn default() -> ModelEvaluation

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for ModelEvaluation

where ModelEvaluation: Default,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Message for ModelEvaluation

fn typename() -> &'static str

The typename of this message.

impl PartialEq for ModelEvaluation

fn eq(&self, other: &ModelEvaluation) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for ModelEvaluation

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for ModelEvaluation