[图书][B] Cluster analysis and applications

For several years, parts of the content of this textbook have been used in undergraduate
courses in the Department of Mathematics and in the Faculty of Economics at the University …

Comparing fuzzy partitions: A generalization of the rand index and related measures

E Hullermeier, M Rifqi, S Henzgen… - IEEE Transactions on …, 2011 - ieeexplore.ieee.org
In this paper, we introduce a fuzzy extension of a class of measures to compare clustering
structures, namely, measures that are based on the number of concordant and the number …

A general framework for evaluating and comparing soft clusterings

A Campagner, D Ciucci, T Denœux - Information Sciences, 2023 - Elsevier
In this article, we propose a general framework for the development of external evaluation
measures for soft clustering. Our proposal is based on the interpretation of soft clustering as …

Partitioning hard clustering algorithms based on multiple dissimilarity matrices

FDAT De Carvalho, Y Lechevallier, FM De Melo - Pattern Recognition, 2012 - Elsevier
This paper introduces hard clustering algorithms that are able to partition objects taking into
account simultaneously their relational descriptions given by multiple dissimilarity matrices …

Fuzzy clustering with weighted medoids for relational data

JP Mei, L Chen - Pattern Recognition, 2010 - Elsevier
The well known k-medoids clustering approach groups objects through finding k
representative objects based on the pairwise (dis) similarities of objects in the data set. In …

Gaussian kernel fuzzy c-means with width parameter computation and regularization

EC Simões, FAT de Carvalho - Pattern Recognition, 2023 - Elsevier
The conventional Gaussian kernel fuzzy c-means clustering algorithms require selecting the
width hyper-parameter, which is data-dependent and fixed for the entire execution. Not only …

A distributional framework for evaluation, comparison and uncertainty quantification in soft clustering

A Campagner, D Ciucci, T Denœux - International Journal of Approximate …, 2023 - Elsevier
In this article, we propose and study a general framework for comparing and evaluating soft
clusterings, viewed as a form of uncertainty quantification for clustering tasks, with the aim of …

Co-clustering of multi-view datasets: a parallelizable approach

G Bisson, C Grimal - 2012 IEEE 12th international conference …, 2012 - ieeexplore.ieee.org
In many applications, entities of the domain are described through different views that
clustering methods often process one by one. We introduce here the architecture MVSim …

Evaluating and comparing soft partitions: An approach based on Dempster–Shafer theory

T Denoeux, S Li, S Sriboonchitta - IEEE Transactions on Fuzzy …, 2017 - ieeexplore.ieee.org
In evidential clustering, cluster-membership uncertainty is represented by Dempster–Shafer
mass functions. The notion of evidential partition generalizes other soft clustering structures …

Gas turbine modeling based on fuzzy clustering algorithm using experimental data

A Benyounes, A Hafaifa, M Guemana - Applied Artificial …, 2016 - Taylor & Francis
The development of reliable mathematical models for nonlinear systems has been a primary
topic in several industrial applications. This work proposes to examine the application of …