Displaying 3 results from an estimated 3 matches for "ibd_prob".
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ibd_probs
2017 Jun 26
3
Jagged ROC curves?
...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
[1] 1.00000000 0.94736842 0.94736842 0.94736842 0.89473684 0.84210526
0.78947368 0.73684211 0.68421053 0.68421053
[11] 0.63157895 0.578947...
2017 Jun 26
0
Jagged ROC curves?
...(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
> [1] 1.00000000 0.94736842 0.94736842 0.94736842 0.89473684 0.84210526
> 0.78947368 0.73684211 0.6...
2017 Jun 26
0
Jagged ROC curves?
...ound(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
> > [1] 1.00000000 0.94736842 0.94736842 0.94736842 0.89473684 0.84...