plsda_roc_plot {structToolbox} | R Documentation

## PLSDA ROC plot

### Description

A Receiver Operator Characteristic (ROC) plot for PLSDA models computed by adjusting the threshold for assigning group labels from PLS predictions.

### Usage

    plsda_roc_plot(factor_name, ...)

### Arguments

`factor_name` | (character) The name of a sample-meta column to use.
`...` | Additional slots and values passed to `struct_class`.

### Details

This object makes use of functionality from the following packages:

- `pls`

- `ggplot2`

### Value

A `plsda_roc_plot` object.

### References

Mevik B, Wehrens R, Liland K (2020). pls: Partial Least Squares and Principal Component Regression. R package version 2.7-3, 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.

### Examples

    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])

[Package structToolbox version 1.2.0 Index]