# ROC analysis, CAFA 2 experiment

My question is about ROC curves used in CAFA2 experiment. In this paper they used the ROC analysis for the term-centric evaluation. In order to perform ROC curve analysis we should have a continuous variable and a classifier (categorical) variable. In CAFA2 experiment, which variables did they consider as a categorical and continuous? Thank you.

$$\begin{array}{@{}rcl@{}} \text{pr}(\tau) &=& \frac{1}{m(\tau)}\sum\limits_{i=1}^{m(\tau)} \frac{{\sum\nolimits}_{f} \unicode{x1D7D9}\left(f \in P_{i}(\tau) \wedge f \in T_{i}\right)}{\sum_{f} \unicode{x1D7D9}\left(f \in P_{i}(\tau) \right)},\\ \text{rc}(\tau) &=& \frac{1}{n_{e}}\sum\limits_{i=1}^{n_{e}} \frac{{\sum\nolimits}_{f} \unicode{x1D7D9}\left(f \in {P}_{i}(\tau) \wedge f \in T_{i}\right)}{{\sum\nolimits}_{f} \unicode{x1D7D9}\left(f \in T_{i} \right)}, \\ F_{\max} &=& \max_{\tau} \left\{ \frac{2\cdot \text{pr}(\tau)\cdot \text{rc}(\tau)}{\text{pr}(\tau) + \text{rc}(\tau)} \right\}, \end{array}$$
where P i (τ) denotes the set of terms that have predicted scores greater than or equal to τ for a protein sequence i, T i denotes the corresponding ground-truth set of terms for that sequence, m(τ) is the number of sequences with at least one predicted score greater than or equal to τ, $\unicode{x1D7D9}\left (\cdot \right)$ is an indicator function, and n e is the number of targets used in a particular mode of evaluation.