Medoid-based shadow value validation and visualization

A silhouette index is a well-known measure of an internal criteria validation for the clustering algorithm results. While it is a medoid-based validation index, a centroid-based validation index that is called a centroid-based shadow value (CSV) has been developed.  Although both are similar, the CS...

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Main Author: Weksi Budiaji
Format: Article
Language:English
Published: Universitas Ahmad Dahlan 2019-04-01
Series:IJAIN (International Journal of Advances in Intelligent Informatics)
Subjects:
Online Access:http://ijain.org/index.php/IJAIN/article/view/326
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author Weksi Budiaji
author_facet Weksi Budiaji
author_sort Weksi Budiaji
collection DOAJ
description A silhouette index is a well-known measure of an internal criteria validation for the clustering algorithm results. While it is a medoid-based validation index, a centroid-based validation index that is called a centroid-based shadow value (CSV) has been developed.  Although both are similar, the CSV has an additional unique property where an image of a 2-dimensional neighborhood graph is possible. A new internal validation index is proposed in this article in order to create a medoid-based validation that has an ability to visualize the results in a 2-dimensional plot. The proposed index behaves similarly to the silhouette index and produces a network visualization, which is comparable to the neighborhood graph of the CSV. The network visualization has a multiplicative parameter (c) to adjust its edges visibility. Due to the medoid-based, in addition, it is more an appropriate visualization technique for any type of data than a neighborhood graph of the CSV.
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spelling doaj.art-f1dd47dcbe854e71937d35e9d82981b02022-12-21T23:40:38ZengUniversitas Ahmad DahlanIJAIN (International Journal of Advances in Intelligent Informatics)2442-65712548-31612019-04-0152768810.26555/ijain.v5i2.326111Medoid-based shadow value validation and visualizationWeksi Budiaji0Sultan Ageng Tirtayasa University, Indonesia; University of Natural Resources and Life SciencesA silhouette index is a well-known measure of an internal criteria validation for the clustering algorithm results. While it is a medoid-based validation index, a centroid-based validation index that is called a centroid-based shadow value (CSV) has been developed.  Although both are similar, the CSV has an additional unique property where an image of a 2-dimensional neighborhood graph is possible. A new internal validation index is proposed in this article in order to create a medoid-based validation that has an ability to visualize the results in a 2-dimensional plot. The proposed index behaves similarly to the silhouette index and produces a network visualization, which is comparable to the neighborhood graph of the CSV. The network visualization has a multiplicative parameter (c) to adjust its edges visibility. Due to the medoid-based, in addition, it is more an appropriate visualization technique for any type of data than a neighborhood graph of the CSV.http://ijain.org/index.php/IJAIN/article/view/326Cluster validationCluster visualizationInternal criteriaMedoidShadow value
spellingShingle Weksi Budiaji
Medoid-based shadow value validation and visualization
IJAIN (International Journal of Advances in Intelligent Informatics)
Cluster validation
Cluster visualization
Internal criteria
Medoid
Shadow value
title Medoid-based shadow value validation and visualization
title_full Medoid-based shadow value validation and visualization
title_fullStr Medoid-based shadow value validation and visualization
title_full_unstemmed Medoid-based shadow value validation and visualization
title_short Medoid-based shadow value validation and visualization
title_sort medoid based shadow value validation and visualization
topic Cluster validation
Cluster visualization
Internal criteria
Medoid
Shadow value
url http://ijain.org/index.php/IJAIN/article/view/326
work_keys_str_mv AT weksibudiaji medoidbasedshadowvaluevalidationandvisualization