reg_rf: Random Forest for regression

In daltoolbox: Leveraging Experiment Lines to Data Analytics

Random Forest for regression

Description

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

Usage

reg_rf(attribute, nodesize = 1, ntree = 10, mtry = NULL)

Arguments

attribute	attribute target to model building
nodesize	node size
ntree	number of trees
mtry	number of attributes to build tree

Value

returns an object of class reg_rfobj

Examples

data(Boston)
model <- reg_rf("medv", ntree=10)

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

model <- fit(model, train)

test_prediction <- predict(model, test)
test_predictand <- test[,"medv"]
test_eval <- evaluate(model, test_predictand, test_prediction)
test_eval$metrics

daltoolbox documentation built on Nov. 3, 2024, 9:06 a.m.