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http://dx.doi.org/10.17703/JCCT.2021.7.3.481

Impact Analysis of Partition Utility Score in Cluster Analysis  

Lee, Gye Sung (Dept. of Software, Dankook Univ)
Publication Information
The Journal of the Convergence on Culture Technology / v.7, no.3, 2021 , pp. 481-486 More about this Journal
Abstract
Machine learning algorithms adopt criterion function as a key component to measure the quality of their model derived from data. Cluster analysis also uses this function to rate the clustering result. All the criterion functions have in general certain types of favoritism in producing high quality clusters. These clusters are then described by attributes and their values. Category utility and partition utility play an important role in cluster analysis. These are fully analyzed in this research particularly in terms of how they are related to the favoritism in the final results. In this research, several data sets are selected and analyzed to show how different results are induced from these criterion functions.
Keywords
Cluster Analysis; Category Utility; Partition Utility; Concept Formation; Knowledge Discovery;
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