Clustering Algorithm For A Healthcare Dataset Using Silhouette Score Value

Godwin Ogbuabor, F. N Ugwoke

Zenodo (CERN European Organization for Nuclear Research) · 2018 · 29 citations · 0 references

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Abstract

The huge amount of healthcare data, coupled with the need for data analysis tools has made data mining interesting research areas. Data mining tools and techniques help to discover and understand hidden patterns in a dataset which may not be possible by mainly visualization of the data. Selecting appropriate clustering method and optimal number of clusters in healthcare data can be confusing and difficult most times. Presently, a large number of clustering algorithms are available for clustering healthcare data, but it is very difficult for people with little knowledge of data mining to choose suitable clustering algorithms