TABLE III.

Selected Methods for Dimensionality Reduction

Method	Advantages	Limitations
Feature extraction: PCA, SVD, tensor-based approaches* [54]	Reduces dimensionality; relatively immune to noise	Performance usually inferior to supervised approaches; difficult to interpret results
Feature selection: filter- based (mRMR), wrapper- based (sequential feature selection)* [55]	Reduces dimensionality; easy to interpret	Sometimes affected by noisy data

^*Highly impactful method with more than 50,000 relevant papers.