Introduction

In Section I, we will discuss the following algorithms:

1. Decision trees

2. Rule-based algorithms

3. Naïve Bayesian algorithm

4. Nearest neighbor algorithm

5. Neural networks

6. Linear discriminant analysis

7. Support vector machine

We will discuss the theoretical aspects of the above-mentioned algorithms as well as the practical MATLAB^® implementations for simple examples. The idea is to provide the readers with simple examples, so that they can start their journey in learning these algorithms in an easy manner. We expect that this will help our readers to build strong foundations and give them insights to have better knowledge of the field.