Struct gapi_grpc::google::cloud::automl::v1beta1::TablesAnnotation[][src]

pub struct TablesAnnotation {
    pub score: f32,
    pub prediction_interval: Option<DoubleRange>,
    pub value: Option<Value>,
    pub tables_model_column_info: Vec<TablesModelColumnInfo>,
    pub baseline_score: f32,
}
[]

Contains annotation details specific to Tables.

Fields

score: f32
[]

Output only. A confidence estimate between 0.0 and 1.0, inclusive. A higher value means greater confidence in the returned value. For

[target_column_spec][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec] of FLOAT64 data type the score is not populated.

prediction_interval: Option<DoubleRange>
[]

Output only. Only populated when

[target_column_spec][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec] has FLOAT64 data type. An interval in which the exactly correct target value has 95% chance to be in.

value: Option<Value>
[]

The predicted value of the row’s

[target_column][google.cloud.automl.v1beta1.TablesModelMetadata.target_column_spec]. The value depends on the column’s DataType:

tables_model_column_info: Vec<TablesModelColumnInfo>
[]

Output only. Auxiliary information for each of the model’s

[input_feature_column_specs][google.cloud.automl.v1beta1.TablesModelMetadata.input_feature_column_specs] with respect to this particular prediction. If no other fields than

[column_spec_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_spec_name] and

[column_display_name][google.cloud.automl.v1beta1.TablesModelColumnInfo.column_display_name] would be populated, then this whole field is not.

baseline_score: f32
[]

Output only. Stores the prediction score for the baseline example, which is defined as the example with all values set to their baseline values. This is used as part of the Sampled Shapley explanation of the model’s prediction. This field is populated only when feature importance is requested. For regression models, this holds the baseline prediction for the baseline example. For classification models, this holds the baseline prediction for the baseline example for the argmax class.

Trait Implementations

impl Clone for TablesAnnotation[src][+]

impl Debug for TablesAnnotation[src][+]

impl Default for TablesAnnotation[src][+]

impl Message for TablesAnnotation[src][+]

impl PartialEq<TablesAnnotation> for TablesAnnotation[src][+]

impl StructuralPartialEq for TablesAnnotation[src]

Auto Trait Implementations

impl RefUnwindSafe for TablesAnnotation

impl Send for TablesAnnotation

impl Sync for TablesAnnotation

impl Unpin for TablesAnnotation

impl UnwindSafe for TablesAnnotation

Blanket Implementations

impl<T> Any for T where
    T: 'static + ?Sized
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impl<T> Borrow<T> for T where
    T: ?Sized
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impl<T> BorrowMut<T> for T where
    T: ?Sized
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impl<T> From<T> for T[src][+]

impl<T> Instrument for T[src][+]

impl<T> Instrument for T[src][+]

impl<T, U> Into<U> for T where
    U: From<T>, 
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impl<T> IntoRequest<T> for T[src][+]

impl<T> ToOwned for T where
    T: Clone
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type Owned = T

The resulting type after obtaining ownership.

impl<T, U> TryFrom<U> for T where
    U: Into<T>, 
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type Error = Infallible

The type returned in the event of a conversion error.

impl<T, U> TryInto<U> for T where
    U: TryFrom<T>, 
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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.

impl<V, T> VZip<V> for T where
    V: MultiLane<T>, 
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impl<T> WithSubscriber for T[src][+]