Unsupervised random forest MDS plot — plotUnsupervisedRF • metabolyseR

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

Usage

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

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

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

Arguments

x: object of class AnalysisData or Analysis
cls: sample information column to use for sample labelling
rf: list of additional parameters to pass to randomForest
label: info 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
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)

## Unsupervised random forest MDS plot
plotUnsupervisedRF(d,cls = 'day')