Supervised random forest MDS plot — plotSupervisedRF • metabolyseR

A multidimensional scaling (MDS) plot of supervised random forest analysis

Usage

plotSupervisedRF(
  x,
  cls = "class",
  rf = list(),
  label = NULL,
  shape = FALSE,
  ellipses = TRUE,
  ROC = TRUE,
  seed = 1234,
  title = "",
  legendPosition = "bottom",
  labelSize = 2,
  ...
)

# S4 method for AnalysisData
plotSupervisedRF(
  x,
  cls = "class",
  rf = list(),
  label = NULL,
  shape = FALSE,
  ellipses = TRUE,
  ROC = TRUE,
  seed = 1234,
  title = "",
  legendPosition = "bottom",
  labelSize = 2
)

# S4 method for Analysis
plotSupervisedRF(
  x,
  cls = "class",
  rf = list(),
  label = NULL,
  shape = FALSE,
  ellipses = TRUE,
  ROC = TRUE,
  seed = 1234,
  title = "",
  legendPosition = "bottom",
  labelSize = 2,
  type = c("pre-treated", "raw")
)

Arguments

x: object of class AnalysisData or Analysis containing analysis results
cls: information column to use for sample classes
rf: list of additional parameters to pass to randomForest
label: information column to use for sample labels. Set to NULL for no labels.
shape: TRUE/FALSE use shape aesthetic for plot points. Defaults to TRUE when the number of classes is greater than 12
ellipses: TRUE/FALSE, plot multivariate normal distribution 95% confidence ellipses for each class
ROC: should receiver-operator characteristics be plotted?
seed: random number seed
title: plot title
legendPosition: legend position to pass to legend.position argument of ggplot2::theme. Set to "none" to remove legend.
labelSize: label size. Ignored if label is NULL
...: arguments to pass to the appropriate method
type: raw or pre-treated data to plot

Examples

library(metaboData)

d <- analysisData(abr1$neg[,200:300],abr1$fact)

## Supervised random forest MDS plot
plotSupervisedRF(d,cls = 'day')