The algorithm is said to be unsupervised when no response is used in the algorithm.
Unsupervised learning can be used:
- for descriptive purposes.
- to find groups of samples that behave similarly,
- to find features that behave similarly,
- to find linear combinations of features with the most variation. (pca ?)
- to classify (Clustering models can be applied to classify cases according to their cluster assignments)