Abstract
One very good, very simple, model for data is to assume that it consists of multiple blobs. To build models like this, we must determine (a) what the blob parameters are and (b) which data points belong to which blob. Generally, we will collect together data points that are close and form blobs out of them. The blobs are usually called clusters , and the process is known as clustering .
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Forsyth, D. (2019). Clustering. In: Applied Machine Learning . Springer, Cham. https://doi.org/10.1007/978-3-030-18114-7_8
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DOI: https://doi.org/10.1007/978-3-030-18114-7_8
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