Add to ORKGCluster analysis consists of applying statistical and heuris-tic methods in an attempt to discover the group composition of a data set. Users of traditional clustering software often find non-intelligent packages difficult to use because of the many parameters that must be specified before an analysis can begin; these include a distance or similarity metric, a method for stopping group amalgama-tion or division, and a particular clustering algorithm. CLUSTERT is an expert system for solving cluster analysis problems that was developed because of this difficulty. Unlike most expert systems, however, CLUSTERT is primarily based on knowledge generated by simulation experiments. The system also provides suggestions and an intelligent environmen...
This is the first book to take a truly comprehensive look at clustering. It begins with an introduct...
PurposeThe purpose of this paper is to provide a review of the issues related to cluster analysis, o...
This book explains and illustrates the most frequently used methods of hierarchical cluster analysis...
Abstract: Clustering is the assignment of data objects (records) into groups (called clusters) so th...
Simulation studies are often used to compare different clustering methods, be it with the aim of pro...
A b s t r a c t K-means clustering algorithms are widely used for many practical applications. Origi...
Cluster Analysis aims at finding subsets (clusters) of a given set of entities, which are homogeneou...
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Common...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...
Abstract. This talk is an attempt at structuring and systematising the develop-ment of clustering as...
45 pages, 1 article*Annotated Computer Output for Illustrative Examples of Clustering Using the Mixt...
Clustering is one of the most useful tasks in data mining process for discovering groups and identif...
10 Clustering is an important data mining problem. However, most earlier work on clustering focused ...
25 pages, 1 article*Illustrative Examples of Clustering Using the Mixture Method and Two Comparable ...
Data analysis plays a prominent role in interpreting various phenomena. Data mining is the process t...
This is the first book to take a truly comprehensive look at clustering. It begins with an introduct...
PurposeThe purpose of this paper is to provide a review of the issues related to cluster analysis, o...
This book explains and illustrates the most frequently used methods of hierarchical cluster analysis...
Abstract: Clustering is the assignment of data objects (records) into groups (called clusters) so th...
Simulation studies are often used to compare different clustering methods, be it with the aim of pro...
A b s t r a c t K-means clustering algorithms are widely used for many practical applications. Origi...
Cluster Analysis aims at finding subsets (clusters) of a given set of entities, which are homogeneou...
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Common...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...
Abstract. This talk is an attempt at structuring and systematising the develop-ment of clustering as...
45 pages, 1 article*Annotated Computer Output for Illustrative Examples of Clustering Using the Mixt...
Clustering is one of the most useful tasks in data mining process for discovering groups and identif...
10 Clustering is an important data mining problem. However, most earlier work on clustering focused ...
25 pages, 1 article*Illustrative Examples of Clustering Using the Mixture Method and Two Comparable ...
Data analysis plays a prominent role in interpreting various phenomena. Data mining is the process t...
This is the first book to take a truly comprehensive look at clustering. It begins with an introduct...
PurposeThe purpose of this paper is to provide a review of the issues related to cluster analysis, o...
This book explains and illustrates the most frequently used methods of hierarchical cluster analysis...