Timeline for What algorithms need feature scaling, beside from SVM?
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jun 15, 2019 at 20:33 | history | edited | kjetil b halvorsen♦ | CC BY-SA 4.0 | added 377 characters in body |
| Oct 25, 2018 at 10:31 | comment | added | kjetil b halvorsen♦ | Can you please add this as a new question? with reference back here! | |
| Oct 25, 2018 at 10:28 | comment | added | Chuck | @kjetil Can I ask you a question building on this? I have a dataset of both categorical and continuous data, for which I'm building an SVM. The continuous data is highly skewed (long tail). For transformation on the continuous should I do a log transformation / Box-Cox and then also normalise the resultant data to get limits between 0 and 1? So i'll be normalising the log values. Then calculate the SVM on the continuous and categorical (0-1) data together? Cheers for any help you can provide | |
| Aug 7, 2018 at 2:35 | comment | added | Mathews24 | Can you explicitly show how one calculates one set of betas from the other in this particular example of scalings you have applied? | |
| Mar 20, 2017 at 10:25 | history | edited | kjetil b halvorsen♦ | CC BY-SA 3.0 | added 24 characters in body |
| Dec 20, 2016 at 21:29 | history | edited | Sycorax♦ | CC BY-SA 3.0 | added 4 characters in body |
| Dec 20, 2016 at 21:09 | history | answered | kjetil b halvorsen♦ | CC BY-SA 3.0 |