cla_rf {daltoolbox}

Random Forest for classification

Description

Creates a classification object that uses the Random Forest method It wraps the randomForest library.

Usage

cla_rf(attribute, slevels, nodesize = 5, ntree = 10, mtry = NULL)

Arguments

attribute

attribute target to model building

slevels

possible values for the target classification

nodesize

node size

ntree

number of trees

mtry

number of attributes to build tree

Value

obj

Examples

data(iris)
slevels <- levels(iris$Species)
model <- cla_rf("Species", slevels, ntree=5)

# preparing dataset for random sampling
sr <- sample_random()
sr <- train_test(sr, iris)
train <- sr$train
test <- sr$test

model <- fit(model, train)

prediction <- predict(model, test)
predictand <- adjust_class_label(test[,"Species"])
test_eval <- evaluate(model, predictand, prediction)
test_eval$metrics