Clusterplot: High-dimensional Cluster Visualization

TL;DR

Clusterplot is a visualization tool that uses 2D blobs to intuitively represent high-dimensional cluster structures and relationships, aiding understanding of complex, overlapping data.

Contribution

It introduces a novel visualization method that effectively depicts high-dimensional cluster relations using supervised 2D blob plots.

Findings

Effective visualization of high-dimensional clusters with complex structures.

Clear depiction of inter-cluster relations such as proximity and overlap.

Enhanced interpretability of high-dimensional data structures.

Abstract

We present Clusterplot, a multi-class high-dimensional data visualization tool designed to visualize cluster-level information offering an intuitive understanding of the cluster inter-relations. Our unique plots leverage 2D blobs devised to convey the geometrical and topological characteristics of clusters within the high-dimensional data, and their pairwise relations, such that general inter-cluster behavior is easily interpretable in the plot. Class identity supervision is utilized to drive the measuring of relations among clusters in high-dimension, particularly, proximity and overlap, which are then reflected spatially through the 2D blobs. We demonstrate the strength of our clusterplots and their ability to deliver a clear and intuitive informative exploration experience for high-dimensional clusters characterized by complex structure and significant overlap.