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Last update: February 19, 2014


PPV/NPV Fitness Function

The PPV/NPV fitness function is based on the positive predictive value (PPV) and negative predictive value (NPV).

The PPV/NPV PNi of an individual program i is evaluated by the equation:

where PPVi is the positive predictive value and NPVi is the negative predictive value of the individual program i, and are given by the formulas:

where TPi, TNi, FPi, and FNi represent, respectively, the number of true positives, true negatives, false positives, and false negatives.

True positives (TP), true negatives (TN), false positives (FP), and false negatives (FN), are the four different possible outcomes of a single prediction for a binomial classification task with classes “1” (“yes”) and “0” (“no”). A false positive is when the outcome is incorrectly classified as “yes” (or “positive”), when it is in fact “no” (or “negative”). A false negative is when the outcome is incorrectly classified as negative when it is in fact positive. True positives and true negatives are obviously correct classifications. These four types of classifications are usually shown in a two-way table called the confusion matrix.

The PPV/NPV fitness function can be combined with a cost matrix in order to impose specific constraints on the solutions. In addition, the evolvable logistic threshold, which is intrinsic to the logistic regression model, can be adjusted by changing the number of bins.

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