Abstract
As the name suggests, unsupervised machine learning does not include finding relationships between input and output. To be honest, there is no output that we try to predict in unsupervised learning. It is mainly used to group together the features that seem to be similar to one another in some sense. These can be the distance between those features or some sort of similarity metric. In this chapter, I will touch on some unsupervised machine learning techniques and build one of the machine learning models, using PySpark to categorize users into groups and, later, to visualize those groups as well.
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© 2019 Pramod Singh
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Singh, P. (2019). Unsupervised Machine Learning. In: Learn PySpark. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-4961-1_7
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DOI: https://doi.org/10.1007/978-1-4842-4961-1_7
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-4960-4
Online ISBN: 978-1-4842-4961-1
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