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// Generated by the protocol buffer compiler.  DO NOT EDIT!
// source: tensorflow_metadata/proto/v0/metric.proto

// Protobuf Java Version: 3.25.4
package org.tensorflow.metadata.v0;

public interface FalseNegativeRateAtThresholdOrBuilder extends
    // @@protoc_insertion_point(interface_extends:tensorflow.metadata.v0.FalseNegativeRateAtThreshold)
    com.google.protobuf.MessageOrBuilder {

  /**
   *    * Threshold to apply to a prediction to determine positive vs negative.
   * Note: if the model is calibrated, the threshold can be thought of as a
   * probability so the threshold has a stable, intuitive semantic.
   * However, not all solutions may be calibrated, and not all computations of
   * the metric may operate on a calibrated score. In AutoTFX, the final model
   * metrics are computed on a calibrated score, but the metrics computed within
   * the model selection process are uncalibrated. Be aware of this possible
   * skew in the metrics between model selection and final model evaluation.
   * 
   *
   * .google.protobuf.DoubleValue threshold = 1;
   * @return Whether the threshold field is set.
   */
  boolean hasThreshold();
  /**
   *    * Threshold to apply to a prediction to determine positive vs negative.
   * Note: if the model is calibrated, the threshold can be thought of as a
   * probability so the threshold has a stable, intuitive semantic.
   * However, not all solutions may be calibrated, and not all computations of
   * the metric may operate on a calibrated score. In AutoTFX, the final model
   * metrics are computed on a calibrated score, but the metrics computed within
   * the model selection process are uncalibrated. Be aware of this possible
   * skew in the metrics between model selection and final model evaluation.
   * 
   *
   * .google.protobuf.DoubleValue threshold = 1;
   * @return The threshold.
   */
  com.google.protobuf.DoubleValue getThreshold();
  /**
   *    * Threshold to apply to a prediction to determine positive vs negative.
   * Note: if the model is calibrated, the threshold can be thought of as a
   * probability so the threshold has a stable, intuitive semantic.
   * However, not all solutions may be calibrated, and not all computations of
   * the metric may operate on a calibrated score. In AutoTFX, the final model
   * metrics are computed on a calibrated score, but the metrics computed within
   * the model selection process are uncalibrated. Be aware of this possible
   * skew in the metrics between model selection and final model evaluation.
   * 
   *
   * .google.protobuf.DoubleValue threshold = 1;
   */
  com.google.protobuf.DoubleValueOrBuilder getThresholdOrBuilder();
}