plsda_roc_plot {structToolbox} | R Documentation |
A Receiver Operator Characteristic (ROC) plot for PLSDA models computed by adjusting the threshold for assigning group labels from PLS predictions.
plsda_roc_plot(factor_name, ...)
factor_name |
(character) The name of a sample-meta column to use. |
... |
Additional slots and values passed to |
This object makes use of functionality from the following packages:
pls
ggplot2
A
plsda_roc_plot
object. This object has no output
slots.
See chart_plot
in the struct
package to plot this chart object.
Liland K, Mevik B, Wehrens R (2021). pls: Partial Least Squares and Principal Component Regression. R package version 2.8-0, https://CRAN.R-project.org/package=pls.
Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.
D = iris_DatasetExperiment() M = mean_centre()+PLSDA(factor_name='Species') M = model_apply(M,D) C = plsda_roc_plot(factor_name='Species') chart_plot(C,M[2])