Abstract
Clusters are subgroups in a survey estimated by the distances between the values needed to connect the patients, otherwise called cases. It is an important methodology in explorative data mining. Density-based clustering is used.
This chapter was previously published in “Machine learning in medicine-cookbook 1” as Chap. 2, Springer Heidelberg Germany, 2013.
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Cleophas, T.J., Zwinderman, A.H. (2020). Density-Based Clustering to Identify Outlier Groups in Otherwise Homogeneous Data (50 Patients). In: Machine Learning in Medicine – A Complete Overview. Springer, Cham. https://doi.org/10.1007/978-3-030-33970-8_2
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DOI: https://doi.org/10.1007/978-3-030-33970-8_2
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