Timeline for LDA for dimensionality reduction usage
Current License: CC BY-SA 3.0
15 events
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| May 7, 2020 at 15:04 | comment | added | aan | @Matthieu thanks. I added here stats.stackexchange.com/questions/464734/… you can answer here I can select your answer | |
| May 7, 2020 at 11:09 | comment | added | Matthieu | @aan please ask a separate question instead of asking by commenting all posts... | |
| May 6, 2020 at 21:23 | comment | added | aan |
Can I know that in the context of dimensionality reduction using LDA/FDA. LDA/FDA can start with n dimensions and end with k dimensions, where k < n. Is that correct? Or The output is c-1 where c is the number of classes and the dimensionality of the data is n with n>c.
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| Jun 22, 2017 at 20:32 | vote | accept | Caio Belfort | ||
| Jun 22, 2017 at 20:32 | vote | accept | Caio Belfort | ||
| Jun 22, 2017 at 20:32 | |||||
| Jun 9, 2017 at 20:49 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| May 10, 2017 at 4:21 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Apr 4, 2017 at 11:29 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Feb 29, 2016 at 17:05 | answer | added | Matthieu | timeline score: 2 | |
| Feb 25, 2016 at 21:36 | comment | added | Caio Belfort | I'm not using LDA for classification. I'm using it for dimension reduction only. | |
| Feb 25, 2016 at 7:48 | comment | added | ttnphns |
You say you are using a svm for classification. But what classification you are using in LDA? LDA uses gaussian linear classifier (a Bayes classifier). You should not mix the methods. If you are comparing classifications as done by all the features and by just discriminants you should use one type of classifier in both cases. Another question to you: I wonder how you managed to run LDA on n=70 < p=96 singular data?
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| Feb 25, 2016 at 7:40 | comment | added | ttnphns | That's as with any modeling. If you want to test on a test dataset you train (model, extract; then classify if you want) the discriminant functions on the train dataset. Then, having their coefficients you compute the functions' values in the test dataset and perform classification by them there. You can then compare classification accuracy in train and test sets. | |
| Feb 25, 2016 at 7:32 | history | edited | ttnphns | CC BY-SA 3.0 |
added 30 characters in body; edited tags
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| Feb 25, 2016 at 4:40 | review | First posts | |||
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| Feb 25, 2016 at 4:35 | history | asked | Caio Belfort | CC BY-SA 3.0 |