Exploratory clustering and visualization

Abstract

In this work the topic of applying clustering as a knowledge extraction method from real-world data is discussed. Authors propose a two-phase cluster creation and visualization technique, which combines hierarchical and density-based algorithms 1. What is more, authors analyze the impact of data sampling on the result of searching through such a structure. Particular attention was also given to the problem of cluster visualization. Authors review selected, two-dimensional approaches, stating their advantages and drawbacks in the context of representing complex cluster structures.