Accelerated Hierarchical Density Clustering

Clustering is the attempt to group data in a way that meets with human intuition. Unfortunately, our intuitive ideas of what makes a'cluster' are poorly defined and highly context sensitive [26]. This results in a plethora of clustering algorithms each of which matches a slightly different intuitive notion of what a natural grouping is. Despite the uncertainty underlying the clustering process it continues to be used in a multitude of scientific domains. The fundamental problem of finding groupings is pervasive and results, however poor, are still important and informative. It is used in diverse fields such as molecular dynamics [40], airplane flight path analysis [60], crystallography [52], and social analytics [29], among many others. While clustering has many uses to many people, our particular focus is on clustering for the purpose of exploratory data analysis. By exploratory data analysis we mean the process of looking for "interesting patterns" in a data set, primarily with the goal of generating new hypotheses or research questions about the data set in question.