This completes the overview of three of the most commonly used unsupervised learning techniques:
Manifold learning for non-linear models is a technically challenging field with great potential in terms of dynamic object recognition [4:18].
The key point to remember is that unsupervised learning techniques are used:
The distinction between unsupervised and supervised learning is not as strict as you may think. For instance, the K-means algorithm can be enhanced to support classification.
In the next chapter, we will address the second use case and cover supervised learning techniques starting with generative models.