An interesting scenario where Principal Component Analysis components are actually easy to interpret, from astrophysics

Every data scientist, especially the ones that find themselves to work with Big Data, knows the importance of dimensionality reduction. If you have a dataset that has a large amount of columns and you have a Machine Learning task to complete:

  • A) The algorithm could take a massive amount of time and energy to perform
  • B) It could perform really badly

So it is important to know and understand some dimensionality reduction techniques and one of the most famous one is the Principal Component Analysis** (P.C.A.).**

#artificial-intelligence #astrophysics #machine-learning #data-science

P.C.A. meets explainability
1.60 GEEK