A Simple and Efficient Method to Compute a Single Linkage Dendrogram

11/01/2019
by   Huanbiao Zhu, et al.
0

We address the problem of computing a single linkage dendrogram. A possible approach is to: (i) Form an edge weighted graph G over the data, with edge weights reflecting dissimilarities. (ii) Calculate the MST T of G. (iii) Break the longest edge of T thereby splitting it into subtrees T_L, T_R. (iv) Apply the splitting process recursively to the subtrees. This approach has the attractive feature that Prim's algorithm for MST construction calculates distances as needed, and hence there is no need to ever store the inter-point distance matrix. The recursive partitioning algorithm requires us to determine the vertices (and edges) of T_L and T_R. We show how this can be done easily and efficiently using information generated by Prim's algorithm without any additional computational cost.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/13/2020

Inset Edges Effect and Average Distance of Trees

An added edge to a graph is called an inset edge. Predicting k inset edg...
research
11/02/2020

Analyzing the Structure of Mondrian's 1920-1940 Compositions

Mondrian was one of the most significant painters of the 20th century. H...
research
08/20/2018

Scalable Edge Partitioning

Edge-centric distributed computations have appeared as a recent techniqu...
research
12/27/2021

Quantum Algorithm for the Longest Trail Problem

We present the quantum algorithm for the Longest Trail Problem. The prob...
research
01/16/2022

Hypergraph Cuts with Edge-Dependent Vertex Weights

We develop a framework for incorporating edge-dependent vertex weights (...
research
04/07/2019

Fast Grid Splitting Detection for N-1 Contingency Analysis by Graph Computing

In this study, a graph-computing based grid splitting detection algorith...
research
02/28/2023

Sequential edge detection using joint hierarchical Bayesian learning

This paper introduces a new sparse Bayesian learning (SBL) algorithm tha...

Please sign up or login with your details

Forgot password? Click here to reset