Clustering-Tutorial

This tutorial seeks to provide a detailed overview of these five different types of clustering:

1. K-means
2. Fuzzy clustering
3. Hierarchical Clustering
4. Density Based Scan Clustering (DBSCAN)
5. Gaussian Mixture Model

We will highlight the differences and practical applications associated with each of these clustering approaches. To illustrate the behavior and nature of various clustering algorithms and techniques, we will use two sample data sets, and coding practice tutorials. The datasets include spatially sampled trajectories of hand written digits from the Open Machine Learning Project, http://archive.ics.uci.edu/ml and spatial data on earthquakes in California from the United States Geological Survey https://earthquake.usgs.gov/earthquakes/search/.