Branching embedding: A heuristic dimensionality reduction algorithm based on hierarchical clustering

2018/05/06 by Makito Oku, Oku, Makito
Computer Science · #Neural Networks and Applications #Face and Expression Recognition #Advanced Clustering Algorithms Research

paper · pdf · doi:10.48550/arxiv.1805.02161

Abstract

This paper proposes a new dimensionality reduction algorithm named branching embedding (BE). It converts a dendrogram to a two-dimensional scatter plot, and visualizes the inherent structures of the original high-dimensional data. Since the conversion part is not computationally demanding, the BE algorithm would be beneficial for the case where hierarchical clustering is already performed. Numerical experiments revealed that the outputs of the algorithm moderately preserve the original hierarchical structures.

Citations

• Multidimensional Scaling by Optimizing Goodness of Fit to a Nonmetric Hypothesis

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