sweeeeeet - 4 months ago 43

R Question

I have a dataframe with two columns :

`score1`

`numeric`

`truth1`

`boolean`

I want to predict

`truth1`

`score1`

`roc_curve = roc(truth1 ~ score1 , data = my_data)`

coords(roc=roc_curve, x = 0.75, input='sensitivity', ret='threshold')

My problem is that coords return 'NA', because the sensitivty of 0.75 does not appear in the ROC curve. So here is my question: how can I get the threshold which gives me a sensitivity of at least 0.75, with max specificity?

Answer

Option 1: you filter the results

```
my.coords <- coords(roc=roc_curve, x = "all")
my.coords[,my.coords["sensitivity",]>=.75]
```

Option 2: you can trick `pROC`

by requesting a partial AUC between 75% and 100% of sensitivity:

```
roc_curve = roc(truth1 ~ score1 , data = my_data, partial.auc = c(1, .75), partial.auc.focus="sensitivity")
```

All other functions will follow and give you results only in this area of interest:

```
coords(roc=roc_curve, x = "local maximas", ret='threshold')
```