Clusterplot: High-dimensional Cluster Visualization
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.
Cite
@article{arxiv.2103.02992,
title = {Clusterplot: High-dimensional Cluster Visualization},
author = {Or Malkai and Min Lu and Daniel Cohen-Or},
journal= {arXiv preprint arXiv:2103.02992},
year = {2021}
}