Details

Further definitions use the following notations:

tp (true positive)

the number of correctly recognized observations for class C 1

tn (true negative)

the number of correctly recognized observations that do not belong to the class C 1

fp (false positive)

the number of observations that were incorrectly assigned to the class C 1

fn (false negative)

the number of observations that were not recognized as belonging to the class C 1

The library uses the following quality metrics for binary classifiers:

Quality Metric

Definition

Accuracy

Precision

Recall

F-score

Specificity

Area under curve (AUC)

For more details of these metrics, including the evaluation focus, refer to [Sokolova09].

The confusion matrix is defined as follows:

Classified as Class C 1

Classified as Class C 2

Actual Class C 1

tp

fn

Actual Class C 2

fp

tn

For more complete information about compiler optimizations, see our Optimization Notice.
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