First commit
Pull cosine nn out to a different file
Implement DBSCAN the first time
Print useful output and bring back inverted index function (required for normalisation)
Add cluster metrics e.g. mean cosine
Add section to help estimate DBSCAN parameters (as per the KDD '96 paper)
Make script to process netflix data and generate more convenient data sets
Create NN index for users instead of items. Also use sparse matrices/vectors
gitignore file