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>Feature selection is well... selecting features. You start with your original 10 features and you pick which ones to use. That sounds a lot like another form
by Frost1x 5y ago
>Feature selection is well... selecting features. You start with your original 10 features and you pick which ones to use.
That sounds a lot like another form of dimensionality reduction to me. The part people trip up on is that dimensions have a very specific definition in the world of statistics. All of these are basically reductionist approaches to tackle representing more complex systems by shedding information, they just go about it in different ways.
- jstx1 5y agoGood point, a look at the contents of the wikipedia page for dimensionality reduction makes it clear - https://en.wikipedia.org/wiki/Dimensionality_reduction https://en.wikipedia.org/wiki/Dimensionality_reduction Dimensionality reduction: 1. Feature selection. 2. Feature projection. 2.1 PCA So you could say that feature selection is dimensionality reduction but you can't say that PCA is feature selection.
- mywittyname 5y ago> but you can't say that PCA is feature selection. One of the steps in PCA is to select the top N eigenvectors sorted by eigenvalues. So while it is not feature selection, it can be argued that it involves a feature selection step.