mccv: mccv class

In RFmarkerDetector: Multivariate Analysis of Metabolomics Data using Random Forests

Description

A constructor function for the S3 class mccv; the mccv class encapsulates information such as predictions and abels needed to plot roc curve(s) for a cross-validated random forest model

Usage

mccv(predictions, labels, models)

Arguments

predictions	a n x p dataframe of the predictions collected during the cross-validation process of the random forest, with n is equal to the number of samples in each test set and p is equal to the number of test sets
labels	a n x p dataframe of the labels of the samples included in each test set obtained splitting the original dataset during the cross-validation process of the model
models	a list of p random forest models tested in the cross-validation process

Value

an object of class mccv

Author(s)

Piergiorgio Palla

Examples

## load a simple dataset with the vectors of the predictions and the labels resulting from a CV 
data(simpleData)
mccv_obj <- mccv(simpleData$predictions, simpleData$labels, models = NULL)

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