Weighted Delta Factor Cluster Ensemble Algorithm for Categorical Data Clustering in Data Mining

N. A.

doi:10.34028/iajit

Article Details

Weighted Delta Factor Cluster Ensemble Algorithm for Categorical Data Clustering in Data Mining

Authors:

N. A.

Publisher:

Zarqa University, Jordan

Journal:

The International Arab Journal of Information Technology (IAJIT) Vol.14 Issue 3, pp.105-114

Document Type:

Article

Publication Date:

1/2017

Document Language:

English

Document ID (Org No.):

2001389043

pISSN:

2309-4524

DOI:

10.34028/iajit

Keywords:

Abstract:

 Though many cluster ensemble approaches came forward as a potential and dominant method for enhancing the 
robustness, stability and the quality of individual clustering systems, it is intensely observed that this approach in most cases 
generate a final data partition with deficient information. The primary ensemble information matrix generated in the 
traditional cluster ensemble approaches results only the cluster data point relations with unknown entries. This paper mainly 
denotes the improved analysis of the Link based Cluster Ensemble (LCE) approach which overcomes the problem of degrading 
the quality of clustering result and in particular it presents an efficient novel Weighted Delta Factor Cluster Ensemble 
algorithm (WDFCE) which enhances the refined matrix by augmenting the values of similitude measures between the clusters 
formed in the Bipartite cluster graph. Subsequently to obtain the final ultimate cluster result, the pairwise-similarity consensus 
method is used in which K-means clustering technique is applied over the similarity measures that are formulated from the 
Refined Similitude Matrix (RSM). Experimental results on few UCI datasets and synthetic dataset reveals that this proposed 
method always outperforms the traditional cluster ensemble techniques and individual clustering algorithms.

Article Details

Weighted Delta Factor Cluster Ensemble Algorithm for Categorical Data Clustering in Data Mining

Authors:

N. A.

Publisher:

Zarqa University, Jordan

Journal:

The International Arab Journal of Information Technology (IAJIT) Vol.14 Issue 3, pp.105-114

Document Type:

Article

Publication Date:

1/2017

Document Language:

English

Document ID (Org No.):

2001389043

pISSN:

2309-4524

DOI:

10.34028/iajit

Clustering

cluster ensembles

consensus function

data mining

refined matrix

similitude measures

Issues

Article Details

Weighted Delta Factor Cluster Ensemble Algorithm for Categorical Data Clustering in Data Mining

Authors: N. A.

Publisher: Zarqa University, Jordan

Journal: The International Arab Journal of Information Technology (IAJIT) Vol.14 Issue 3, pp.105-114

Document Type: Article

Publication Date: 1/2017

Document Language: English

Document ID (Org No.): 2001389043

pISSN: 2309-4524

DOI: 10.34028/iajit

Clustering

cluster ensembles

consensus function

data mining

refined matrix

similitude measures

Issues

Authors:

N. A.

Publisher:

Zarqa University, Jordan

Journal:

The International Arab Journal of Information Technology (IAJIT) Vol.14 Issue 3, pp.105-114

Document Type:

Article

Publication Date:

1/2017

Document Language:

English

Document ID (Org No.):

2001389043

pISSN:

2309-4524

DOI:

10.34028/iajit