# ROC curve
# input a two factor variables
y_pred = as.factor(c(1,0,0,1,0,1,1,0,0,1,1,0,0,1,0,1,1,0,0,1,1,0,0,1,0,1,1,0,0,1))
y_obs = as.factor(c(1,1,0,1,0,0,0,1,0,0,1,1,0,1,0,0,0,1,0,0,1,1,0,1,0,0,0,1,0,0))
y_pred = rep(1, times = 100)
y_obs = rep(1, times = 100)
TPR = numeric(length(y_obs))
FPR = numeric(length(y_pred))
for (i in 1:length(y_obs)){
# subset the vectors
thres_pred = y_pred[1:i]
thres_obs = y_obs[1:i]
# calculate the TPR and FPR
TPRi = unlist(evaluation_metrics(y_obs = thres_obs,
y_pred = thres_pred,
type = "classification")[8])
FPRi = unlist(evaluation_metrics(y_obs = thres_obs,
y_pred = thres_pred,
type = "classification")[9])
# append TPRi and FPRi to TPR and FPR
TPR = c(TPR, TPRi)
FPR = c(FPR, FPRi)
}
plot(y = TPR, x = FPR, type = "l")
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