prelim_ML: prelim.ML

In IFIproteomics/E2Predictor:

Description

makes some preliminary steps useful for Machine Learning (A PCA and a correlation analysis)

Usage

prelim_ML(df, ncp = 5, dim.reduction.factor = 0.7, save.to = NULL,
  suffix = "")

Arguments

df	data frame for analysis
ncp	number of dimensions kept in the results (by default 5) of PCA analysis
dim.reduction.factor	Correlation threshold over which correlated variables will be dropped
save.to	when not NULL, folder path where result files will be written
suffix	when save.to is not NULL, it adds a suffix to file names

Value

list with max four objects: PCA and correlation of variables, and if variable reduction is possible, PCA and correlation of reduced variables.

IFIproteomics/E2Predictor documentation built on May 8, 2019, 10:54 a.m.