RandomEAT {eat}

Individual EAT for Random Forest

Description

This function builds an individual tree for Random Forest

Usage

RandomEAT(data, x, y, numStop, s_mtry)

Arguments

data

data.frame containing the training set.

x

Vector. Column input indexes in data.

y

Vector. Column output indexes in data.

numStop

Minimum number of observations in a node for a split to be attempted.

s_mtry

Number of variables randomly sampled as candidates at each split. The available options are: "BRM", "DEA1", "DEA2", "DEA3", "DEA4" or any integer.

Value

A list of m trees in forest and the error that will be used in the ranking of the importance of the variables.