- Two versions with different similarily matrices (k-nearest, gaussian similarity)
- Implementation of both k-nearest and gaussian similarity graphs
- Calculating Degree and Laplacian + running k-means on the first k eigenvectors
- Data visualization support for 2D data sets through graphing clusters via colors
- 3 sample sets with 2D data and full results (generated with draw-data python package)
This project was done as part of coursework for 21-241(Matrices and Linear Transformations) with Claire Chen.