plotSupervisedRF: Supervised random forest MDS plot

plotSupervisedRFR Documentation

Supervised random forest MDS plot

Description

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 signature '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 signature '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')

jasenfinch/metabolyseR documentation built on Sept. 18, 2023, 1:25 a.m.