Results 51 to 60 of about 3,381,889 (354)
Covariance matrix filtering with bootstrapped hierarchies.
PLoS ONE, 2021 Cleaning covariance matrices is a highly non-trivial problem, yet of central importance in the statistical inference of dependence between objects. We propose here a probabilistic hierarchical clustering method, named Bootstrapped Average Hierarchical ...
Christian Bongiorno, Damien Challet
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Divisive hierarchical maximum likelihood clustering
BMC Bioinformatics, 2017 Background Biological data comprises various topologies or a mixture of forms, which makes its analysis extremely complicated. With this data increasing in a daily basis, the design and development of efficient and accurate statistical methods has become
Alok Sharma +2 more
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genieclust: Fast and robust hierarchical clustering
SoftwareX, 2021 genieclust is an open source Python and R package that implements the hierarchical clustering algorithm called Genie. This method frequently outperforms other state-of-the-art approaches in terms of clustering quality and speed, supports various ...
Marek Gagolewski
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Higra: Hierarchical Graph Analysis
SoftwareX, 2019 Higra — Hierarchical Graph Analysis is a C++/Python library for efficient sparse graph analysis with a special focus on hierarchical methods capable of handling large amount of data.
B. Perret +5 more
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Scalable adaptive hierarchical clustering [PDF]
IEEE Communications Letters, 2002 We propose a new application-level clustering algorithm capable of building an overlay spanning tree among participants of large multicast sessions, without any specific help from the network routers. This algorithm is based on a unique definition of zones around nodes and an innovative adaptive cluster size distribution.
MATHY L. +3 more
openaire +4 more sources
A Quantitative Clustering Approach to Ultrametricity in Spin Glasses [PDF]
, 2003 We discuss the problem of ultrametricity in mean field spin glasses by means of a hierarchical clustering algorithm. We complement the clustering approach with quantitative testing: we discuss both in some detail.
Ciliberti, Stefano, Marinari, Enzo
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Semantic Clustering of Functional Requirements Using Agglomerative Hierarchical Clustering
Information, 2018 Software applications have become a fundamental part in the daily work of modern society as they meet different needs of users in different domains.
Hamzeh Eyal Salman +3 more
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Tree Structured Dirichlet Processes for Hierarchical Morphological Segmentation [PDF]
Computational Linguistics, 2018 This article presents a probabilistic hierarchical clustering model for morphological segmentation. In contrast to existing approaches to morphology learning, our method allows learning hierarchical organization of word morphology as a collection of tree
Burcu Can, Suresh Manandhar
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Scalable Hierarchical Clustering with Tree Grafting [PDF]
Knowledge Discovery and Data Mining, 2019 We introduce Grinch, a new algorithm for large-scale, non-greedy hierarchical clustering with general linkage functions that compute arbitrary similarity between two point sets.
Nicholas Monath +4 more
semanticscholar +1 more source
On morphological hierarchical representations for image processing and spatial data clustering
, 2012 Hierarchical data representations in the context of classi cation and data clustering were put forward during the fties. Recently, hierarchical image representations have gained renewed interest for segmentation purposes. In this paper, we briefly survey
A. Baraldi +75 more
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