rF_testing: A random forest classifier training and testing function

In samrabi1/ada.classification: Classification Methods: K-means and Random Forests

Description

This function allows one to perform random forest classification (see randomForest for more information regarding the function to perform this classification method) of varying models on a training and testing set of the original data, the size of which is defined by the user.

Usage

rF_testing(dat, s, x, model)

Arguments

dat	dataset to perform test on
s	proportion of dataset to be assigned to the 'training' dataset
x	the classifying variable in the dataset
model	written in the style of a regression, defines the classifying variable and the predictors the user wants to use to perform the test

Examples

rF_testing(dat = iris, s = 0.5, x = Species,
model = Species ~ Petal.Length + Petal.Width + Sepal.Length)

samrabi1/ada.classification documentation built on May 23, 2020, 7:01 a.m.