The purpose of this project is to explore some techniques in supervised learning. It is important to realize that understanding an algorithm or technique requires understanding how it behaves under a variety of circumstances. Objective is to implement some simple learning algorithms, and to compare their performance.
Implemented using R and Tableau.
Six supervised learning algorithms are implemented. -> Decision trees -> Neural networks -> k Nearest neightbors -> Boosting -> Support vector machines -> Naive bayes classification