Skip to contents

plot_ml_roc

Source: R/plot_ml_roc.R
plot_ml_roc.Rd

This function generates the overall ROC curve for cross-validations (CVs) with varying feature numbers and the ROC curve for the average CVs based on user-selected feature numbers.

Usage

plot_ml_roc(ml_se, feature_num = 10)

Arguments

ml_se

A SummarizedExperiment object with results computed by ml_model.

feature_num

Numeric. The number of features to be shown in the plots. A feature number value selected from feature_option of the SummarizedExperiment object returned by ml_model. Usually be one of 2, 3, 5, 10, 20, 50, 100. Default is 10.

Value

Return 2 interactive plots, 2 static plots, and 2 data frames.

  1. interactive_mean_auc & static_mean_auc: ROC curve plots

  2. initeractive_roc & static_roc: ROC Curve of average CVs plots

  3. table_mean_auc_plot: ROC data frame of n features

  4. table_roc: average ROC curve plot of n features

Examples

data("ml_se_sub")
res <- plot_ml_roc(ml_se_sub, feature_num=10)