Struct EntityRecognizerEvaluationMetricsBuilder

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#[non_exhaustive]
pub struct EntityRecognizerEvaluationMetricsBuilder { /* private fields */ }

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A builder for EntityRecognizerEvaluationMetrics.

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impl EntityRecognizerEvaluationMetricsBuilder

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pub fn precision(self, input: f64) -> Self

A measure of the usefulness of the recognizer results in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones.

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pub fn set_precision(self, input: Option<f64>) -> Self

A measure of the usefulness of the recognizer results in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones.

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pub fn get_precision(&self) -> &Option<f64>

A measure of the usefulness of the recognizer results in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones.

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pub fn recall(self, input: f64) -> Self

A measure of how complete the recognizer results are for the test data. High recall means that the recognizer returned most of the relevant results.

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pub fn set_recall(self, input: Option<f64>) -> Self

A measure of how complete the recognizer results are for the test data. High recall means that the recognizer returned most of the relevant results.

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pub fn get_recall(&self) -> &Option<f64>

A measure of how complete the recognizer results are for the test data. High recall means that the recognizer returned most of the relevant results.

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pub fn f1_score(self, input: f64) -> Self

A measure of how accurate the recognizer results are for the test data. It is derived from the Precision and Recall values. The F1Score is the harmonic average of the two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best score. For PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score.

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pub fn set_f1_score(self, input: Option<f64>) -> Self

A measure of how accurate the recognizer results are for the test data. It is derived from the Precision and Recall values. The F1Score is the harmonic average of the two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best score. For PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score.

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pub fn get_f1_score(&self) -> &Option<f64>

A measure of how accurate the recognizer results are for the test data. It is derived from the Precision and Recall values. The F1Score is the harmonic average of the two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best score. For PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score.

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pub fn build(self) -> EntityRecognizerEvaluationMetrics

Consumes the builder and constructs a EntityRecognizerEvaluationMetrics.

Trait Implementations§

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impl Clone for EntityRecognizerEvaluationMetricsBuilder

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fn clone(&self) -> EntityRecognizerEvaluationMetricsBuilder

Returns a duplicate of the value. Read more

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

Performs copy-assignment from source. Read more

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impl Debug for EntityRecognizerEvaluationMetricsBuilder

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

Formats the value using the given formatter. Read more

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impl Default for EntityRecognizerEvaluationMetricsBuilder

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fn default() -> EntityRecognizerEvaluationMetricsBuilder

Returns the “default value” for a type. Read more

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impl PartialEq for EntityRecognizerEvaluationMetricsBuilder

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

Tests for self and other values to be equal, and is used by ==.

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

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

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impl StructuralPartialEq for EntityRecognizerEvaluationMetricsBuilder

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impl UnwindSafe for EntityRecognizerEvaluationMetricsBuilder

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Struct EntityRecognizerEvaluationMetricsBuilderCopy item path

Implementations§

impl EntityRecognizerEvaluationMetricsBuilder

pub fn precision(self, input: f64) -> Self

pub fn set_precision(self, input: Option<f64>) -> Self

pub fn get_precision(&self) -> &Option<f64>

pub fn recall(self, input: f64) -> Self

pub fn set_recall(self, input: Option<f64>) -> Self

pub fn get_recall(&self) -> &Option<f64>

pub fn f1_score(self, input: f64) -> Self

pub fn set_f1_score(self, input: Option<f64>) -> Self

pub fn get_f1_score(&self) -> &Option<f64>

pub fn build(self) -> EntityRecognizerEvaluationMetrics

Trait Implementations§

impl Clone for EntityRecognizerEvaluationMetricsBuilder

fn clone(&self) -> EntityRecognizerEvaluationMetricsBuilder

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

impl Debug for EntityRecognizerEvaluationMetricsBuilder

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

impl Default for EntityRecognizerEvaluationMetricsBuilder

fn default() -> EntityRecognizerEvaluationMetricsBuilder

impl PartialEq for EntityRecognizerEvaluationMetricsBuilder

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

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

impl StructuralPartialEq for EntityRecognizerEvaluationMetricsBuilder

Auto Trait Implementations§

impl Freeze for EntityRecognizerEvaluationMetricsBuilder

impl RefUnwindSafe for EntityRecognizerEvaluationMetricsBuilder

impl Send for EntityRecognizerEvaluationMetricsBuilder

impl Sync for EntityRecognizerEvaluationMetricsBuilder

impl Unpin for EntityRecognizerEvaluationMetricsBuilder

impl UnwindSafe for EntityRecognizerEvaluationMetricsBuilder

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Struct EntityRecognizerEvaluationMetricsBuilder

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