rsdFilter: Filtering less informative variables

In RFmarkerDetector: Multivariate Analysis of Metabolomics Data using Random Forests

Description

rsdFilter removes from the dataframe the predictors with a relative standard deviation less than or equal to an inserted threshold

Usage

rsdFilter(data, threshold, exclude = T)

Arguments

data	a n x p data frame with n observations and p columns. While the first two columns usually represent the names of the samples and the class labels related to each sample respectively, the remaining columns represent metabolite concentrations measured by 1H NMR or bins of 1H NMR spectra
threshold	a numeric value representing a limit: each predictor with a relative standard deviation lower than that will be removed form the dataframe
exclude	a logical variable which stores a simple True / False setting. If set to True the filtering method will exclude the first two columns.

Value

a list containing the filtered dataset, a vector with the names of the varables excluded and a vector with the indexes of the variables eliminated

Author(s)

Piergiorgio Palla

Examples

 ## load the included example dataset
data(cachexiaData)
## call rsdFilter with the parameter exclude set to TRUE (default) 
## in order to exclude the first two columns of the dataset from scaling
data.filtered <- rsdFilter(cachexiaData, threshold = 15, exclude = TRUE)

RFmarkerDetector documentation built on May 2, 2019, 3:42 p.m.