A Guide for Supervised Learning Methods

A Quarto Book that provides guidance for machine learning methods and advanced data visualiziation in R. For each method the theory behind it is explained and an example of usage in R is given. https://eddabra.github.io/guides-for-supervised-learning/

Index:

1. Introduction
2. Visualization
3. Model accuracy and Fit
4. Linear Regression
5. Classification
6. Beyond Linearity
7. Tree-based Methods
8. Text Mining

Based on the course “Applied Data Analysis & Visualisation” from the Department of Methodology and Statistics (University Utrecht).