Unsupervised Learning Models

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Unsupervised learning models are composed of features that are not associated with a response. This means that this type of machine learning algorithms do not have labelled data as their interest lies in the attributes of the features themselves.

In unsupervised learning models there is no concept of training or supervising a dataset as the independent variables or features (x1,x2,x3,..,xn)) are not paired with a response (y). The goal of these problems is to model the underlying structure or distribution of the data to learn more about it.