Theory of Generalisation

Unsupervised learning is a kind of machine learning algorithm that can be used to draw useful conclusions without the presence of labeled responses in the input data. In the previous chapter, we discussed clustering (k-means clustering, hierarchical clustering) and Principal Component Analysis. In this chapter, we will discuss training versus testing, bounding the testing error, and the VC dimension.