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Based on: https://blog.revolutionanalytics.com/2016/08/roc-curves-in-two-lines-of-code.html
calcAUC(modelPredictions, yValues, ..., na.rm = FALSE, yTarget = TRUE)
numeric predictions (not empty), ordered (either increasing or decreasing)
truth values (not empty, same length as model predictions)
force later arguments to bind by name.
logical, if TRUE remove NA values.
value considered to be positive.
area under curve
# NOT RUN { sigr::calcAUC(1:4, c(TRUE,FALSE,TRUE,TRUE)) # should be 2/3 # }
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