software.amazon.awssdk.services.comprehend.model

Interface ClassifierEvaluationMetrics.Builder

All Superinterfaces:

Buildable, CopyableBuilder<ClassifierEvaluationMetrics.Builder,ClassifierEvaluationMetrics>, SdkBuilder<ClassifierEvaluationMetrics.Builder,ClassifierEvaluationMetrics>, SdkPojo

Enclosing class:

ClassifierEvaluationMetrics

public static interface ClassifierEvaluationMetrics.Builder
extends SdkPojo, CopyableBuilder<ClassifierEvaluationMetrics.Builder,ClassifierEvaluationMetrics>

Method Summary

Modifier and Type	Method and Description
ClassifierEvaluationMetrics.Builder	accuracy(Double accuracy) The fraction of the labels that were correct recognized.
ClassifierEvaluationMetrics.Builder	f1Score(Double f1Score) A measure of how accurate the classifier results are for the test data.
ClassifierEvaluationMetrics.Builder	precision(Double precision) A measure of the usefulness of the classifier results in the test data.
ClassifierEvaluationMetrics.Builder	recall(Double recall) A measure of how complete the classifier results are for the test data.

Methods inherited from interface software.amazon.awssdk.core.SdkPojo

sdkFields

Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder

copy

Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder

applyMutation, build

Method Detail

accuracy

ClassifierEvaluationMetrics.Builder accuracy(Double accuracy)

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.

Parameters:

accuracy - 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.

Returns:

Returns a reference to this object so that method calls can be chained together.

precision

ClassifierEvaluationMetrics.Builder precision(Double precision)

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.

Parameters:

precision - 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.

Returns:

Returns a reference to this object so that method calls can be chained together.

recall

ClassifierEvaluationMetrics.Builder recall(Double recall)

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.

Parameters:

recall - 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.

Returns:

Returns a reference to this object so that method calls can be chained together.

f1Score

ClassifierEvaluationMetrics.Builder f1Score(Double f1Score)

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.

Parameters:

f1Score - 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.

Returns:

Returns a reference to this object so that method calls can be chained together.