Displaying 3 results from an estimated 3 matches for "roc_1".
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proc_1
2017 Jun 26
3
Jagged ROC curves?
...la= status ~ ., data=d1train,
ranking='MDA',ntree=1000,pdel=0.05)
my_opt_model <- my_model$RFopt
my_probs <- predict(my_opt_model, d1test, type = 'prob')
my_roc <- roc(d1test[,resp_col] ~ my_probs[,2])
aucval <- round(as.numeric(my_roc$auc),4)
return(my_roc)
}
roc_1 <- getROC(dat1,dat1test)
plot.roc(roc_1,col="brown3")
> roc_1
Call:
roc.formula(formula = d1test[, resp_col] ~ ibd_probs[, 2])
Data: ibd_probs[, 2] in 3 controls (d1test[, resp_col] 0) < 19 cases
(d1test[, resp_col] 1).
Area under the curve: 0.8596
> roc_1$sensitivities...
2017 Jun 26
0
Jagged ROC curves?
...',ntree=1000,pdel=0.05)
> my_opt_model <- my_model$RFopt
>
> my_probs <- predict(my_opt_model, d1test, type = 'prob')
> my_roc <- roc(d1test[,resp_col] ~ my_probs[,2])
> aucval <- round(as.numeric(my_roc$auc),4)
> return(my_roc)
> }
>
>
> roc_1 <- getROC(dat1,dat1test)
> plot.roc(roc_1,col="brown3")
>
>
>> roc_1
>
> Call:
> roc.formula(formula = d1test[, resp_col] ~ ibd_probs[, 2])
>
> Data: ibd_probs[, 2] in 3 controls (d1test[, resp_col] 0) < 19 cases
> (d1test[, resp_col] 1).
> Ar...
2017 Jun 26
0
Jagged ROC curves?
...> For the attached two png files (test_roc.png & test_roc_smooth.png)
>
> 1. Using 'plot' function:
>
> plot(c(1,0),c(0,1), type='l', lty=3, xlim=c(1.01,-0.01), ylim=c(-0.01,1.01), xaxs='i', yaxs='i', ylab='', xlab='')
> plot(roc_1,col="brown3", lwd=2, add=T, lty=1)
>
> 2. Using the 'smooth' function:
>
> plot(c(1,0),c(0,1), type='l', lty=3, xlim=c(1.01,-0.01), ylim=c(-0.01,1.01), xaxs='i', yaxs='i', ylab='', xlab='')
> plot(smooth(roc_1),col="bro...