Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...

C. Radhakrishna Rao, The Use and Interpretation of Principal Component Analysis in Applied Research, Sankhyā: The Indian Journal of Statistics, Series A (1961-2002), Vol. 26, No. 4 (Dec., 1964), pp.

Principal component analysis is often incorporated into genome-wide expression studies, but what is it and how can it be used to explore high-dimensional data?

It emerges that representations using the proposed derivative principal component analysis recover the underlying derivatives more accurately compared to principal component analysis-based approaches ...