Makito Oku

1paper

1 Paper

MLMay 6, 2018
Branching embedding: A heuristic dimensionality reduction algorithm based on hierarchical clustering

Makito Oku

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.