Add to ORKGCluster Analysis for Applications deals with methods and various applications of cluster analysis. Topics covered range from variables and scales to measures of association among variables and among data units. Conceptual problems in cluster analysis are discussed, along with hierarchical and non-hierarchical clustering methods. The necessary elements of data analysis, statistics, cluster analysis, and computer implementation are integrated vertically to cover the complete path from raw data to a finished analysis.Comprised of 10 chapters, this book begins with an introduction to the subject
Given a set of entities, Cluster Analysis aims at finding subsets, called clusters, which are homoge...
A cluster analysis computer program is presented which uses the K-Means algorithm to obtain partitio...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...
This book explains and illustrates the most frequently used methods of hierarchical cluster analysis...
This paper analyzes the versatility of 10 dif-ferent popular programs which contain hierarchical met...
This paper analyzes the versatility of 10 dif-ferent popular programs which contain hierarchical met...
The aim of this master's thesis was to get acquainted with cluster analysis, clustering methods and ...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
Clustering is one of the most useful tasks in data mining process for discovering groups and identif...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
This paper analyzes the versatility of 10 different popular programs which contain hierarchical me...
Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By o...
This work is an overview of some of the most frequently used algorithms for cluster analysis and som...
PurposeThe purpose of this paper is to provide a review of the issues related to cluster analysis, o...
Given a set of entities, Cluster Analysis aims at finding subsets, called clusters, which are homoge...
Given a set of entities, Cluster Analysis aims at finding subsets, called clusters, which are homoge...
A cluster analysis computer program is presented which uses the K-Means algorithm to obtain partitio...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...
This book explains and illustrates the most frequently used methods of hierarchical cluster analysis...
This paper analyzes the versatility of 10 dif-ferent popular programs which contain hierarchical met...
This paper analyzes the versatility of 10 dif-ferent popular programs which contain hierarchical met...
The aim of this master's thesis was to get acquainted with cluster analysis, clustering methods and ...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
Clustering is one of the most useful tasks in data mining process for discovering groups and identif...
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research devel...
This paper analyzes the versatility of 10 different popular programs which contain hierarchical me...
Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By o...
This work is an overview of some of the most frequently used algorithms for cluster analysis and som...
PurposeThe purpose of this paper is to provide a review of the issues related to cluster analysis, o...
Given a set of entities, Cluster Analysis aims at finding subsets, called clusters, which are homoge...
Given a set of entities, Cluster Analysis aims at finding subsets, called clusters, which are homoge...
A cluster analysis computer program is presented which uses the K-Means algorithm to obtain partitio...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...