This chapter focuses on unsupervised machine learning, which typically deals with unlabelled data. The objective is to somehow sort these data into similar groups based on common feature(s). Often, although not always, unsupervised machine learning also is used as a type of dimension reduction. For example, if you get a dataset with hundreds or thousands of features, but only a few thousand cases, you may wish to first utilize unsupervised learning to distil the large number of features into a smaller number ...
© Matt Wiley and Joshua F. Wiley 2019
Matt Wiley and Joshua F. WileyAdvanced R Statistical Programming and Data Modelshttps://doi.org/10.1007/978-1-4842-2872-2_77. ML: Unsupervised
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