Struct google_api_proto::google::cloud::automl::v1beta1::classification_evaluation_metrics::ConfidenceMetricsEntry

pub struct ConfidenceMetricsEntry {

    pub confidence_threshold: f32,
    pub position_threshold: i32,
    pub recall: f32,
    pub precision: f32,
    pub false_positive_rate: f32,
    pub f1_score: f32,
    pub recall_at1: f32,
    pub precision_at1: f32,
    pub false_positive_rate_at1: f32,
    pub f1_score_at1: f32,
    pub true_positive_count: i64,
    pub false_positive_count: i64,
    pub false_negative_count: i64,
    pub true_negative_count: i64,
}

Metrics for a single confidence threshold.

Fields

confidence_threshold: f32

Output only. Metrics are computed with an assumption that the model never returns predictions with score lower than this value.

position_threshold: i32

Output only. Metrics are computed with an assumption that the model always returns at most this many predictions (ordered by their score, descendingly), but they all still need to meet the confidence_threshold.

recall: f32

Output only. Recall (True Positive Rate) for the given confidence threshold.

precision: f32

Output only. Precision for the given confidence threshold.

false_positive_rate: f32

Output only. False Positive Rate for the given confidence threshold.

f1_score: f32

Output only. The harmonic mean of recall and precision.

recall_at1: f32

Output only. The Recall (True Positive Rate) when only considering the label that has the highest prediction score and not below the confidence threshold for each example.

precision_at1: f32

Output only. The precision when only considering the label that has the highest prediction score and not below the confidence threshold for each example.

false_positive_rate_at1: f32

Output only. The False Positive Rate when only considering the label that has the highest prediction score and not below the confidence threshold for each example.

f1_score_at1: f32

Output only. The harmonic mean of [recall_at1][google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.recall_at1] and [precision_at1][google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.precision_at1].

true_positive_count: i64

Output only. The number of model created labels that match a ground truth label.

false_positive_count: i64

Output only. The number of model created labels that do not match a ground truth label.

false_negative_count: i64

Output only. The number of ground truth labels that are not matched by a model created label.

true_negative_count: i64

Output only. The number of labels that were not created by the model, but if they would, they would not match a ground truth label.

Trait Implementations

impl Clone for ConfidenceMetricsEntry

fn clone(&self) -> ConfidenceMetricsEntry

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for ConfidenceMetricsEntry

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

Formats the value using the given formatter.

impl Default for ConfidenceMetricsEntry

fn default() -> Self

Returns the “default value” for a type.

impl Message for ConfidenceMetricsEntry

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(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where 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( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where 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(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

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

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

where Self: Sized,

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

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

where Self: Sized,

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

impl PartialEq for ConfidenceMetricsEntry

fn eq(&self, other: &ConfidenceMetricsEntry) -> 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 Copy for ConfidenceMetricsEntry

impl StructuralPartialEq for ConfidenceMetricsEntry