The problem of finding groups in data (cluster analysis) has been extensively studied by researchers from the fields of Statistics and Computer Science, among others. However, despite its popularity it is widely recognized that the investigation of some theoretical aspects of clustering has been relatively sparse. One of the main reasons for this lack of theoretical results is surely the fact that, unlike the situation with other statistical problems as regression or classification, for some of the cluster methodologies it is quite difficult to specify a population goal to which the data-based clustering algorithms should try to get close. This paper aims to provide some insight into the theoretical foundations of the usual nonparametric ap...
International audienceThe aim of this work is to define a clustering method starting from thepretopo...
We formulate clustering as a minimisation problem in the space of measures by modelling the cluster ...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
The idea underlying modal clustering is to associate groups with the regions around the modes of the...
The density-based formulation aims at recasting the clustering problem to a mathematically sound fra...
Given a set of objects X a clustering algorithm is a formal procedure that groups together objects w...
Kleinberg introduced three natural clustering properties, or axioms, and showed they cannot be simul...
A new clustering approach based on mode identification is developed by applying new optimization tec...
Model-based clustering has been widely used for clustering heterogeneous populations. But standard m...
Cluster Analysis aims at finding subsets (clusters) of a given set of entities, which are homogeneou...
The goal of clustering is to detect the presence of distinct groups in a data set and assign group l...
Clustering is a division of data into groups of similar objects. Representing the data by fewer clus...
Cluster analysis seeks to identify homogeneous subgroups of cases in a population. This article prov...
Clustering is the unsupervised classification of patterns (observations, data items, or feature vect...
In 2009, Yu et al. proposed a multimodal probability model (MPM) for clustering. This paper makes ad...
International audienceThe aim of this work is to define a clustering method starting from thepretopo...
We formulate clustering as a minimisation problem in the space of measures by modelling the cluster ...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
The idea underlying modal clustering is to associate groups with the regions around the modes of the...
The density-based formulation aims at recasting the clustering problem to a mathematically sound fra...
Given a set of objects X a clustering algorithm is a formal procedure that groups together objects w...
Kleinberg introduced three natural clustering properties, or axioms, and showed they cannot be simul...
A new clustering approach based on mode identification is developed by applying new optimization tec...
Model-based clustering has been widely used for clustering heterogeneous populations. But standard m...
Cluster Analysis aims at finding subsets (clusters) of a given set of entities, which are homogeneou...
The goal of clustering is to detect the presence of distinct groups in a data set and assign group l...
Clustering is a division of data into groups of similar objects. Representing the data by fewer clus...
Cluster analysis seeks to identify homogeneous subgroups of cases in a population. This article prov...
Clustering is the unsupervised classification of patterns (observations, data items, or feature vect...
In 2009, Yu et al. proposed a multimodal probability model (MPM) for clustering. This paper makes ad...
International audienceThe aim of this work is to define a clustering method starting from thepretopo...
We formulate clustering as a minimisation problem in the space of measures by modelling the cluster ...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...