Struct gcp_client::google::cloud::automl::v1beta1::ModelEvaluation

pub struct ModelEvaluation {
    pub name: String,
    pub annotation_spec_id: String,
    pub display_name: String,
    pub create_time: Option<Timestamp>,
    pub evaluated_example_count: i32,
    pub metrics: Option<Metrics>,
}

Evaluation results of a model.

Fields

name: String

Output only. Resource name of the model evaluation. Format:

projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}

annotation_spec_id: String

Output only. The ID of the annotation spec that the model evaluation applies to. The The ID is empty for the overall model evaluation. For Tables annotation specs in the dataset do not exist and this ID is always not set, but for CLASSIFICATION

[prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] the [display_name][google.cloud.automl.v1beta1.ModelEvaluation.display_name] field is used.

display_name: String

Output only. The value of [display_name][google.cloud.automl.v1beta1.AnnotationSpec.display_name] at the moment when the model was trained. Because this field returns a value at model training time, for different models trained from the same dataset, the values may differ, since display names could had been changed between the two model's trainings. For Tables CLASSIFICATION

[prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] distinct values of the target column at the moment of the model evaluation are populated here. The display_name is empty for the overall model evaluation.

create_time: Option<Timestamp>

Output only. Timestamp when this model evaluation was created.

evaluated_example_count: i32

Output only. The number of examples used for model evaluation, i.e. for which ground truth from time of model creation is compared against the predicted annotations created by the model. For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is the total number of all examples used for evaluation. Otherwise, this is the count of examples that according to the ground truth were annotated by the

[annotation_spec_id][google.cloud.automl.v1beta1.ModelEvaluation.annotation_spec_id].

metrics: Option<Metrics>

Output only. Problem type specific evaluation metrics.

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 Message for ModelEvaluation

fn encode_raw<B>(&self, buf: &mut B) where
    B: BufMut, 

fn merge_field<B>(
    &mut self,
    tag: u32,
    wire_type: WireType,
    buf: &mut B,
    ctx: DecodeContext
) -> Result<(), DecodeError> where
    B: Buf, 

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode<B>(&self, buf: &mut B) -> Result<(), EncodeError> where
    B: BufMut, 

Encodes the message to a buffer.

fn encode_length_delimited<B>(&self, buf: &mut B) -> Result<(), EncodeError> where
    B: BufMut, 

Encodes the message with a length-delimiter to a buffer.

fn decode<B>(buf: B) -> Result<Self, DecodeError> where
    B: Buf,
    Self: Default, 

Decodes an instance of the message from a buffer.

fn decode_length_delimited<B>(buf: B) -> Result<Self, DecodeError> where
    B: Buf,
    Self: Default, 

Decodes a length-delimited instance of the message from the buffer.

fn merge<B>(&mut self, buf: B) -> Result<(), DecodeError> where
    B: Buf, 

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited<B>(&mut self, buf: B) -> Result<(), DecodeError> where
    B: Buf, 

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq<ModelEvaluation> for ModelEvaluation

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

This method tests for self and other values to be equal, and is used by ==.

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

This method tests for !=.

impl StructuralPartialEq for ModelEvaluation