Aside from clustering, unsupervised learning can also perform dimensionality reduction. You can use dimensionality reduction when you have a dataset with too many features.

A clustering problem is an unsupervised learning problem that asks the model to find groups ... Autoencoders have been used for dimensionality reduction, feature learning, de-noising, anomaly ...

This paper visualizes the entire quantitative investment strategies (QIS) universe in a risk-premia-segmented two-dimensional space.We propose and implement a dimensionality reduction model, for a ...