Add to ORKGThe literature on cluster analysis has a long and rich history in several different fields. In this paper, we provide an overview of the more well-known clustering methods frequently used to analyse ordinal data.We summarize and compare their main features discussing some key issues. Finally, an example of application to real data is illustrated comparing and discussing clustering performances of different methods
Abstract: This article made a brief comparative survey of modern cluster-ing algorithms quantitative...
Clustering is a division of data into groups of similar objects. Representing the data by fewer clus...
A mixture model for ordinal data modelling (denoted CUB) has been recently proposed in literature. S...
The literature on cluster analysis has a long and rich history in several different fields. In this ...
Clustering ordinal data is a common task in data mining and machine learning fields. As a major type...
Ordinal data are used in a lot of domains, especially when measurements are collected from persons b...
This article presents a testing procedure for comparing ordinal data distributions which helps the i...
Cluster Analysis is a well established methodology in Marketing research to perform market segmenta...
Cluster analysis may be considered as an aid to decision theory because of its ability to group the ...
Considerable progress in methodology development for the analysis of ordinal response data has been ...
Abstract The chapter by Milligan and Hirtle provides an overview of the current state of knowledge i...
This thesis represents an original contribution to knowledge on ordinal data, which constitutes the ...
International audienceThis book offers an original and broad exploration of the fundamental methods ...
International audienceOrdinal data are used in many domains, especially when measurements are collec...
Cluster analysis or clustering is a task of grouping a set of objects in such a way that objects in ...
Abstract: This article made a brief comparative survey of modern cluster-ing algorithms quantitative...
Clustering is a division of data into groups of similar objects. Representing the data by fewer clus...
A mixture model for ordinal data modelling (denoted CUB) has been recently proposed in literature. S...
The literature on cluster analysis has a long and rich history in several different fields. In this ...
Clustering ordinal data is a common task in data mining and machine learning fields. As a major type...
Ordinal data are used in a lot of domains, especially when measurements are collected from persons b...
This article presents a testing procedure for comparing ordinal data distributions which helps the i...
Cluster Analysis is a well established methodology in Marketing research to perform market segmenta...
Cluster analysis may be considered as an aid to decision theory because of its ability to group the ...
Considerable progress in methodology development for the analysis of ordinal response data has been ...
Abstract The chapter by Milligan and Hirtle provides an overview of the current state of knowledge i...
This thesis represents an original contribution to knowledge on ordinal data, which constitutes the ...
International audienceThis book offers an original and broad exploration of the fundamental methods ...
International audienceOrdinal data are used in many domains, especially when measurements are collec...
Cluster analysis or clustering is a task of grouping a set of objects in such a way that objects in ...
Abstract: This article made a brief comparative survey of modern cluster-ing algorithms quantitative...
Clustering is a division of data into groups of similar objects. Representing the data by fewer clus...
A mixture model for ordinal data modelling (denoted CUB) has been recently proposed in literature. S...