PCA: Bioinformatician’s Favorite Tool Can Be Misleading

Author(s): Salvatore Raieli

Originally published on Towards AI.

A new study assesses how a most used technique can be problematic

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Photo by NASA on Unsplash

The principal component analysis (PCA)is a popular machine learning technique used for complexity reduction, but according to some researchers, it is unreliable and inconsistent and may be part of the reproducibility crisis in science.

The reproducibility crisis in science has been increasingly discussed in recent years. There are several reasons why science is not reproducible, but some may also be the fault of the misuse of machine learning.

For one, the data themselves are often uncurated. In cancer research, this has become a problem. Access is not… Read the full blog for free on Medium.

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Published via Towards AI