A Simple and Efficient Method to Compute a Single Linkage Dendrogram
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.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Maximum Likelihood Estimation for Single Linkage Hierarchical Clustering
We derive a statistical model for estimation of a dendrogram from single linkage hierarchical clustering (SLHC) that takes account of uncertainty through noise or corruption in the measurements of separation of data. Our…
ClusteringSmall Data Image ClassificationPANDORA: A Parallel Dendrogram Construction Algorithm for Single Linkage Clustering on GPU
This paper presents \pandora, a novel parallel algorithm for efficiently constructing dendrograms for single-linkage hierarchical clustering, including \hdbscan. Traditional dendrogram construction methods from a minimum…
ClusteringGPUHierarchical clustering with OWA-based linkages, the Lance-Williams formula, and dendrogram inversions
Agglomerative hierarchical clustering based on Ordered Weighted Averaging (OWA) operators not only generalises the single, complete, and average linkages, but also includes intercluster distances based on a few nearest o…
Clusteringmdendro: An R package for extended agglomerative hierarchical clustering
"mdendro" is an R package that provides a comprehensive collection of linkage methods for agglomerative hierarchical clustering on a matrix of proximity data (distances or similarities), returning a multifurcated dendrog…
ClusteringDescriptiveOrder preserving hierarchical agglomerative clustering
Partial orders and directed acyclic graphs are commonly recurring data structures that arise naturally in numerous domains and applications and are used to represent ordered relations between entities in the domains. Exa…
Clustering