Kaufman and Rousseeuw (1990) define cluster analysis as the classification of similar objects into groups, where the number of groups, as well as their forms are unknown. The “form of a group ” refers to the parameters of cluster; that is, to its cluster-specific means, variances, and covariances that also have a geometrical interpretation. A similar definition is given by Everit
Abstract: The interpretation of cluster analysis solutions in the case of objectattribute data can b...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
PurposeThe purpose of this paper is to provide a review of the issues related to cluster analysis, o...
Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By o...
Cluster analysis can not only cluster observations/cases into several groups but also cluster variab...
Cluster Analysis aims at finding subsets (clusters) of a given set of entities, which are homogeneou...
The problem of taking a set of data and separating it into subgroups where the elements of each subg...
This book explains and illustrates the most frequently used methods of hierarchical cluster analysis...
Cluster and discriminant analysis belong to basic classification methods. Using cluster analysis can...
Cluster analysis is a fundamental principle in exploratory data analysis, providing the user with a ...
<p>Agglomerative hierarchical cluster analysis for the whole data set to define the natural division...
Clustering has become an increasingly popular method of multivariate analysis over the past two deca...
Clustering is one of the most useful tasks in data mining process for discovering groups and identif...
Clustering seeks to group or to lump together objects or variables that share some observed qualitie...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...
Abstract: The interpretation of cluster analysis solutions in the case of objectattribute data can b...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
PurposeThe purpose of this paper is to provide a review of the issues related to cluster analysis, o...
Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By o...
Cluster analysis can not only cluster observations/cases into several groups but also cluster variab...
Cluster Analysis aims at finding subsets (clusters) of a given set of entities, which are homogeneou...
The problem of taking a set of data and separating it into subgroups where the elements of each subg...
This book explains and illustrates the most frequently used methods of hierarchical cluster analysis...
Cluster and discriminant analysis belong to basic classification methods. Using cluster analysis can...
Cluster analysis is a fundamental principle in exploratory data analysis, providing the user with a ...
<p>Agglomerative hierarchical cluster analysis for the whole data set to define the natural division...
Clustering has become an increasingly popular method of multivariate analysis over the past two deca...
Clustering is one of the most useful tasks in data mining process for discovering groups and identif...
Clustering seeks to group or to lump together objects or variables that share some observed qualitie...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...
Abstract: The interpretation of cluster analysis solutions in the case of objectattribute data can b...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
PurposeThe purpose of this paper is to provide a review of the issues related to cluster analysis, o...