Timeline for Pull out most important variables from PCA
Current License: CC BY-SA 3.0
13 events
| when toggle format | what | by | license | comment | |
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| Jun 11, 2020 at 14:32 | history | edited | CommunityBot |
Commonmark migration
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| Jan 23, 2015 at 16:09 | history | edited | Scortchi♦ | CC BY-SA 3.0 |
fixed typos
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| Jul 18, 2014 at 15:53 | comment | added | jayk | In your case, loadings might show how much a certain keyword indicates a paper fits into a latent category. Scores would then show how much the paper fits into that category. Papers having (high values of) variables with high loadings for PCA1 should have higher PCA1 scores as the score of a paper is just the vector product of the loadings and that paper's variables. | |
| Jul 17, 2014 at 16:18 | comment | added | biotech | It's more clear now, thanks! Last question: Do papers having variables with high (and positive) loadings have then lower PCA1 scores? (and viceversa for papers not having them) | |
| Jul 17, 2014 at 15:38 | vote | accept | biotech | ||
| Jul 17, 2014 at 15:26 | history | edited | jayk | CC BY-SA 3.0 |
added 89 characters in body
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| Jul 17, 2014 at 15:21 | comment | added | jayk | I've edited the response to reflect this. | |
| Jul 17, 2014 at 15:20 | history | edited | jayk | CC BY-SA 3.0 |
Edit to reflect selecting variables from principle components
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| Jul 17, 2014 at 9:34 | comment | added | biotech | Is it OK to look at the loadings in PC1 for all the variables and get the variables with values further from zero? Also, I don't well know how to interpret loadings. | |
| Jul 17, 2014 at 9:29 | comment | added | biotech | Thanks for you response j-kahn. What I mean is that I'm looking for the original variables that are more important to discriminate papers in PC1. | |
| Jul 16, 2014 at 20:20 | history | undeleted | jayk | ||
| Jul 16, 2014 at 16:39 | history | deleted | jayk | via Vote | |
| Jul 16, 2014 at 16:35 | history | answered | jayk | CC BY-SA 3.0 |