Struct google_api_proto::google::cloud::automl::v1beta1::TablesAnnotation

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:

• CATEGORY - the predicted (with the above confidence score) CATEGORY value.

• FLOAT64 - the predicted (with above prediction_interval) FLOAT64 value.

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

fn clone(&self) -> TablesAnnotation

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for TablesAnnotation

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

Formats the value using the given formatter.

impl Default for TablesAnnotation

fn default() -> Self

Returns the “default value” for a type.

impl Message for TablesAnnotation

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, Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

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

where B: BufMut, Self: Sized,

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

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated 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, Self: Sized,

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, Self: Sized,

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

impl PartialEq for TablesAnnotation

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

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

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

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

impl StructuralPartialEq for TablesAnnotation