Jupyter notebook files for a machine learning project in the course COGS 118A Supervised Machine Learning Algorithms. In short the object of this project was to empirically test different machine learning algorithms using a variety of data sets from the UCI Machine Learning Repository.
- Resulting paper from project: COGS118A___Final_Project_HEADLINEFIXED.pdf
- Folder Tomasspangelo.finalproject contains all jupyter notebook files and data. Each jupyter notebook corresponds to a data set, where the data set is prepared and preprocessed and then the three machine learning algorithms k-NN, random forests and suport vector machine are run on the dataset. Results are presented in each notebook at the bottom using heatmaps etc. from parameter tuning using cross validation.