One of the major problems in clustering is the need of specifying the optimal number of clusters in some clustering algorithms. Some block clustering algorithms suffer from the same limitation that the number of clusters needs to be specified by a human user. This problem has been subject of wide research. Numerous indices were proposed in order to find reasonable number of clusters. In this paper, we aim to extend the use of these indices to block clustering algorithms. Therefore, an examination of some indices for determining the number of clusters in CROKI2 algorithm is conducted on synthetic data sets. The purpose of the paper is to test the performance and ability of some indices to detect the proper number of clusters on rows and colu...
Master of ScienceDepartment of Computing and Information SciencesWilliam H. HsuThe project explores ...
Abstract — The true use of clustering is not exploited properly as humans try to cluster datasets wh...
In this paper we present an unsupervised algorithm which performs clustering given a data set and wh...
Abstract: One of the major problems in clustering is the need of specifying the optimal number of cl...
An examination of 14 indexes for determining the number of clusters is conducted on artificial binar...
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Clustering procedures partiti...
An examination of 14 indexes for determining the number of clusters is conducted on articial binary ...
The diploma thesis explores with the evaluation of the success of selected indices for determining t...
This presentation proposes a maximum clustering similarity (MCS) method for determining the number o...
Abstract: The K-means algorithm is a popular data-clustering algorithm. However, one of its drawback...
Determining the number of clusters in a dataset has been one of the most challenging problems in clu...
Abstract: A fundamental and difficult problem in cluster analysis is the determination of the “true...
The objective of this thesis is the evaluation of selected coefficients of the cluster analysis when...
Abstract: It is essential to know the parameters required to clustering the dataset. One of the para...
This thesis considers four important issues in cluster analysis: cluster validation, estimation of ...
Master of ScienceDepartment of Computing and Information SciencesWilliam H. HsuThe project explores ...
Abstract — The true use of clustering is not exploited properly as humans try to cluster datasets wh...
In this paper we present an unsupervised algorithm which performs clustering given a data set and wh...
Abstract: One of the major problems in clustering is the need of specifying the optimal number of cl...
An examination of 14 indexes for determining the number of clusters is conducted on artificial binar...
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Clustering procedures partiti...
An examination of 14 indexes for determining the number of clusters is conducted on articial binary ...
The diploma thesis explores with the evaluation of the success of selected indices for determining t...
This presentation proposes a maximum clustering similarity (MCS) method for determining the number o...
Abstract: The K-means algorithm is a popular data-clustering algorithm. However, one of its drawback...
Determining the number of clusters in a dataset has been one of the most challenging problems in clu...
Abstract: A fundamental and difficult problem in cluster analysis is the determination of the “true...
The objective of this thesis is the evaluation of selected coefficients of the cluster analysis when...
Abstract: It is essential to know the parameters required to clustering the dataset. One of the para...
This thesis considers four important issues in cluster analysis: cluster validation, estimation of ...
Master of ScienceDepartment of Computing and Information SciencesWilliam H. HsuThe project explores ...
Abstract — The true use of clustering is not exploited properly as humans try to cluster datasets wh...
In this paper we present an unsupervised algorithm which performs clustering given a data set and wh...