Package smile.validation.metric
Class Specificity
java.lang.Object
smile.validation.metric.Specificity
- All Implemented Interfaces:
Serializable
,ToDoubleBiFunction<int[],
,int[]> ClassificationMetric
Specificity (SPC) or True Negative Rate is a statistical measures of the
performance of a binary classification test. Specificity measures the
proportion of negatives which are correctly identified.
SPC = TN / N = TN / (FP + TN) = 1 - FPRSensitivity and specificity are closely related to the concepts of type I and type II errors. For any test, there is usually a trade-off between the measures. This trade-off can be represented graphically using an ROC curve.
In this implementation, the class label 1 is regarded as positive and 0 is regarded as negative.
- See Also:
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Field Details
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instance
Default instance.
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Constructor Details
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Specificity
public Specificity()
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Method Details
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score
public double score(int[] truth, int[] prediction) Description copied from interface:ClassificationMetric
Returns a score to measure the quality of classification.- Specified by:
score
in interfaceClassificationMetric
- Parameters:
truth
- the true class labels.prediction
- the predicted class labels.- Returns:
- the metric.
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of
public static double of(int[] truth, int[] prediction) Calculates the specificity.- Parameters:
truth
- the ground truth.prediction
- the prediction.- Returns:
- the metric.
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toString
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