rankingRFEAT: Ranking of variables by Random Forest + Efficiency Analysis...

In eat: Efficiency Analysis Trees

Ranking of variables by Random Forest + Efficiency Analysis Trees model.

Description

This function calculates variable importance through a Random Forest + Efficiency Analysis Trees model.

Usage

rankingRFEAT(object, barplot = TRUE, digits = 2)

Arguments

object	A RFEAT object.
barplot	logical. If TRUE, a barplot with importance scores is displayed.
digits	Decimal units.

Value

data.frame with the importance scores and a barplot representing the variable importance if barplot = TRUE.

Examples

simulated <- X2Y2.sim(N = 50, border = 0.2)
RFEAT_model <- RFEAT(data = simulated, x = c(1,2), y = c(3, 4))

rankingRFEAT(object = RFEAT_model,
             barplot = TRUE,
             digits = 2)

eat documentation built on Jan. 10, 2023, 5:13 p.m.