Like Principal Components Analysis? New Paper Reports It Can Produce “Phantom Oscillation” Artifacts

Principal Component Analysis (PCA), a widely used statistical method for simplifying complex datasets, has been found to produce “phantom oscillations” — patterns that appear in the data although they don’t exist in the original data set. Read on to know more about this, of special relevance to you if you are used to applying PCA on datasets with the features discussed. This also constitutes a chance to overview other limitations and disadvantages of PCA.