Struct google_bigquery2::api::EvaluationMetrics

pub struct EvaluationMetrics {
    pub arima_forecasting_metrics: Option<ArimaForecastingMetrics>,
    pub binary_classification_metrics: Option<BinaryClassificationMetrics>,
    pub clustering_metrics: Option<ClusteringMetrics>,
    pub dimensionality_reduction_metrics: Option<DimensionalityReductionMetrics>,
    pub multi_class_classification_metrics: Option<MultiClassClassificationMetrics>,
    pub ranking_metrics: Option<RankingMetrics>,
    pub regression_metrics: Option<RegressionMetrics>,
}

Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models.

This type is not used in any activity, and only used as part of another schema.

Fields

arima_forecasting_metrics: Option<ArimaForecastingMetrics>

Populated for ARIMA models.

binary_classification_metrics: Option<BinaryClassificationMetrics>

Populated for binary classification/classifier models.

clustering_metrics: Option<ClusteringMetrics>

Populated for clustering models.

dimensionality_reduction_metrics: Option<DimensionalityReductionMetrics>

Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.

multi_class_classification_metrics: Option<MultiClassClassificationMetrics>

Populated for multi-class classification/classifier models.

ranking_metrics: Option<RankingMetrics>

Populated for implicit feedback type matrix factorization models.

regression_metrics: Option<RegressionMetrics>

Populated for regression models and explicit feedback type matrix factorization models.

Trait Implementations

impl Clone for EvaluationMetrics

fn clone(&self) -> EvaluationMetrics

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for EvaluationMetrics

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

Formats the value using the given formatter.

impl Default for EvaluationMetrics

fn default() -> EvaluationMetrics

Returns the "default value" for a type.

impl<'de> Deserialize<'de> for EvaluationMetrics

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl Part for EvaluationMetrics

impl Serialize for EvaluationMetrics

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

Serialize this value into the given Serde serializer.