Chapter 8 Measuring Performance

To compare different models, we need a way to measure model performance. There are various metrics to use. To better understand the strengths and weaknesses of a model, you need to look at it through multiple metrics. In this chapter, we will introduce some of the most common performance measurement metrics.

Load the R packages first:

# install packages from CRAN
p_needed <- c('caret', 'dplyr', 'randomForest',
              'readr', 'car', 'pROC', 'fmsb', 'caret')

packages <- rownames(installed.packages())
p_to_install <- p_needed[!(p_needed %in% packages)]

if (length(p_to_install) > 0) {

lapply(p_needed, require, character.only = TRUE)