Displaying 3 results from an estimated 3 matches for "resp_col".
2017 Jun 26
3
Jagged ROC curves?
...rary(pROC)
library(AUCRF)
getROC <- function(d1train,d1test){
my_model <- AUCRF(formula= 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) <...
2017 Jun 26
0
Jagged ROC curves?
...getROC <- function(d1train,d1test){
> my_model <- AUCRF(formula= 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])
&...
2017 Jun 26
0
Jagged ROC curves?
...,d1test){
> > my_model <- AUCRF(formula= 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:
> >...