Principal Components Analysis and Latent Variable Models

In the previous chapter we introduced two unsupervised methods that could be used to perform clustering – the partitioning of data objects into a finite number of disjoint groups such that objects in the same group share some similarity. We now turn our attention to a second class of unsupervised methods that could broadly be classed as projection techniques.