Clustering Using OPTICS

A seemingly parameter-less algorithm

See What I Did There?

Clustering is a powerful unsupervised knowledge discovery tool used today, which aims to segment your data points into groups of similar features. However, each algorithm is pretty sensitive to the parameters. Similarity based techniques (K-means, etc) are tasked with designating how many clusters exist, while hierarchical usually require manual intervention to…