plot_roc: Plot ROC

In GenomeNet/deepG: Deep Learning for Genome Sequence Data

Plot ROC

Description

Compute ROC and AUC from target and prediction matrix and plot ROC. Target/prediction matrix should have one column if output of layer with sigmoid activation and two columns for softmax activation.

Usage

plot_roc(y_true, y_conf, path_roc_plot = NULL, return_plot = TRUE)

Arguments

y_true	Matrix of true labels.
y_conf	Matrix of predictions.
path_roc_plot	Where to store ROC plot.
return_plot	Whether to return plot.

Value

A ggplot of ROC curve.

Examples

y_true <- matrix(c(1, 0, 0, 0, 1, 1), ncol = 1)
y_conf <- matrix(runif(n = nrow(y_true)), ncol = 1)
p <- plot_roc(y_true, y_conf, return_plot = TRUE)
p

GenomeNet/deepG documentation built on Dec. 24, 2024, 12:11 p.m.