Timeline for How to prove that text is linearly separable?
Current License: CC BY-SA 3.0
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| Jun 5, 2015 at 6:24 | comment | added | Marc Claesen | @ml_guy it is not wrong per se, as the RBF kernel can yield at least comparable performance. However, training a model with RBF kernel takes a lot more time and you would have to tune the kernel bandwidth, which takes orders of magnitude more time than training a linear model. Hence, using an RBF kernel on high dimensional data is usually a waste of computational effort. You can see a similar reasoning in A practical guide for SVM classification (appendix C). | |
| Jun 5, 2015 at 6:22 | comment | added | tumbleweed | Sure, I tried with the Linear kernel and my metrics increasead amazingly.... Do you think is wrong to use the RBF kernel for text, in particular opinions?. | |
| Jun 5, 2015 at 6:06 | history | edited | Marc Claesen | CC BY-SA 3.0 |
added 232 characters in body
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| Jun 5, 2015 at 6:00 | history | answered | Marc Claesen | CC BY-SA 3.0 |