What is PCA? When do you use it?

1.	What is PCA? When do you use it?
Answer» Principal component analysis (PCA) is most commonly USED for dimension reduction. In this case, PCA measures the VARIATION in each variable (or column in the table). If there is little variation, it throws the variable out, as illustrated in the figure below: Principal component analysis (PCA) Thus making the DATASET easier to visualize. PCA is used in FINANCE, neuroscience, and pharmacology. It is very useful as a preprocessing STEP, especially when there are linear correlations between features.

Answer»

Principal component analysis (PCA) is most commonly USED for dimension reduction.

In this case, PCA measures the VARIATION in each variable (or column in the table). If there is little variation, it throws the variable out, as illustrated in the figure below:

Principal component analysis (PCA)

Thus making the DATASET easier to visualize. PCA is used in FINANCE, neuroscience, and pharmacology.

It is very useful as a preprocessing STEP, especially when there are linear correlations between features.

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