mds: Multidimensional scaling (MDS)

In jasenfinch/metabolyseR: Methods for Pre-Treatment, Data Mining and Correlation Analyses of Metabolomics Data

Multidimensional scaling (MDS)

Description

Multidimensional scaling of random forest proximities.

Usage

mds(x, dimensions = 2, idx = NULL)

## S4 method for signature 'RandomForest'
mds(x, dimensions = 2, idx = NULL)

## S4 method for signature 'list'
mds(x, dimensions = 2, idx = NULL)

## S4 method for signature 'Analysis'
mds(x, dimensions = 2, idx = NULL)

Arguments

x	S4 object of class RandomForest, Analysis or a list
dimensions	The number of dimensions by which the data are to be represented.
idx	sample information column to use for sample names. If NULL, the sample row number will be used. Sample names should be unique for each row of data.

Value

A tibble containing the scaled dimensions.

Examples

library(metaboData)

x <- analysisData(abr1$neg[,200:300],abr1$fact) %>%
       occupancyMaximum(cls = 'day') %>%
       transformTICnorm()
       
rf <- randomForest(x,cls = 'day')

mds(rf)

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