f_riskScorePerformance
Arguments: binary outcome variable obj_outcome whose dimensions are the same as obj_testScore.
Ouputs: test results (true positives, true negatives, false positives, and false negatives of a test).
The novelty is the speed of this function. The populations of true/false positives and true/false negatives are calculated without deploying any iterations over the entire population (which can require, e.g., 30 minutes to iterate over a population of 10^6).
I found this highly useful when I wrote home-brew machine learning code in MATLAB. I needed to calculate sensitivity, specificity, positive/negative predictive values, and concordance.
Cita come
bradley Nartowt (2026). f_riskScorePerformance (https://it.mathworks.com/matlabcentral/fileexchange/73713-f_riskscoreperformance), MATLAB Central File Exchange. Recuperato .
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| Versione | Pubblicato | Note della release | |
|---|---|---|---|
| 1.0.0 |
