Workshop 9: More classifiers

We’ll be looking at some more classifiers, all of which you have met before:

• k-nearest neighbours
• trees and forests
• neural networks

As always, we’ll use the tidymodels framework for fitting, estimating classes and for model accuracy.

We’ll use the glass dataset you are already familiar with, along with some new data from a palaeographic analysis of the “Avila” Bible produced during the XII century between Italy and Spain.

Start by downloading lab09.Rmd and load it into RStudio:

https://www.massey.ac.nz/~jcmarsha/161324/labs/lab09.Rmd

Ensure the document knits correctly, then work your way through the R Markdown worksheet.