Analysis of Different Supervised Machine Learning Methods

This is my project from my cogs 118a: supervised machine learning class. Our project was to analyze different datasets using machine learning methods. For my project, I decided to analyze some popular ML datasets: Adult, Letter (which was divided into 2 subsets), and Skin. I used Random Forest, KNN, and Logistic Regression algorithms to classify these datasets. In total, I think the algorithms ran rather well, with Random Forest being the fastest. I’ll probably add more to this analysis at a later point, I think a comparison of the datasets could be done in a more holistic manner than I did. I also have the report I wrote along with my groupmate (who did 3 other Supervised ML algorithms) on this project in the github page, if you are interested.