[][src]Struct rusoto_comprehend::ClassifierEvaluationMetrics

pub struct ClassifierEvaluationMetrics {
    pub accuracy: Option<f64>,
    pub f1_score: Option<f64>,
    pub precision: Option<f64>,
    pub recall: Option<f64>,
}

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.

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 PartialEq<ClassifierEvaluationMetrics> for ClassifierEvaluationMetrics[src]

impl Default for ClassifierEvaluationMetrics[src]

impl Clone for ClassifierEvaluationMetrics[src]

fn clone_from(&mut self, source: &Self)
1.0.0
[src]

Performs copy-assignment from source. Read more

impl Debug for ClassifierEvaluationMetrics[src]

impl<'de> Deserialize<'de> for ClassifierEvaluationMetrics[src]

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