[−][src]Struct rusoto_comprehend::ClassifierEvaluationMetrics
Describes the result metrics for the test data associated with an documentation classifier.
Fields
accuracy: Option<f64>
The fraction of the labels that were correct recognized. It is computed by dividing the number of labels in the test documents that were correctly recognized by the total number of labels in the test documents.
f1_score: Option<f64>
A measure of how accurate the classifier 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. The highest score is 1, and the worst score is 0.
hamming_loss: Option<f64>
Indicates the fraction of labels that are incorrectly predicted. Also seen as the fraction of wrong labels compared to the total number of labels. Scores closer to zero are better.
micro_f1_score: Option<f64>
A measure of how accurate the classifier results are for the test data. It is a combination of the Micro Precision
and Micro Recall
values. The Micro F1Score
is the harmonic mean of the two scores. The highest score is 1, and the worst score is 0.
micro_precision: 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. Unlike the Precision metric which comes from averaging the precision of all available labels, this is based on the overall score of all precision scores added together.
micro_recall: Option<f64>
A measure of how complete the classifier results are for the test data. High recall means that the classifier returned most of the relevant results. Specifically, this indicates how many of the correct categories in the text that the model can predict. It is a percentage of correct categories in the text that can found. Instead of averaging the recall scores of all labels (as with Recall), micro Recall is based on the overall score of all recall scores added together.
precision: Option<f64>
A measure of the usefulness of the classifier results in the test data. High precision means that the classifier returned substantially more relevant results than irrelevant ones.
recall: Option<f64>
A measure of how complete the classifier results are for the test data. High recall means that the classifier returned most of the relevant results.
Trait Implementations
impl Clone for ClassifierEvaluationMetrics
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pub fn clone(&self) -> ClassifierEvaluationMetrics
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pub fn clone_from(&mut self, source: &Self)
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impl Debug for ClassifierEvaluationMetrics
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impl Default for ClassifierEvaluationMetrics
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pub fn default() -> ClassifierEvaluationMetrics
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impl<'de> Deserialize<'de> for ClassifierEvaluationMetrics
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pub fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
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__D: Deserializer<'de>,
impl PartialEq<ClassifierEvaluationMetrics> for ClassifierEvaluationMetrics
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pub fn eq(&self, other: &ClassifierEvaluationMetrics) -> bool
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pub fn ne(&self, other: &ClassifierEvaluationMetrics) -> bool
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impl StructuralPartialEq for ClassifierEvaluationMetrics
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Auto Trait Implementations
impl RefUnwindSafe for ClassifierEvaluationMetrics
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impl Send for ClassifierEvaluationMetrics
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impl Sync for ClassifierEvaluationMetrics
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impl Unpin for ClassifierEvaluationMetrics
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impl UnwindSafe for ClassifierEvaluationMetrics
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Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
pub fn borrow_mut(&mut self) -> &mut T
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impl<T> DeserializeOwned for T where
T: for<'de> Deserialize<'de>,
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T: for<'de> Deserialize<'de>,
impl<T> From<T> for T
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impl<T> Instrument for T
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pub fn instrument(self, span: Span) -> Instrumented<Self>
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pub fn in_current_span(self) -> Instrumented<Self>
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T> Same<T> for T
type Output = T
Should always be Self
impl<T> ToOwned for T where
T: Clone,
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T: Clone,
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T
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pub fn clone_into(&self, target: &mut T)
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impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,