Timeline for Support Vector Machines as Neural Nets?
Current License: CC BY-SA 3.0
4 events
| when toggle format | what | by | license | comment | |
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| Sep 26, 2014 at 4:17 | comment | added | Aaron | I believe you are correct that the kernel function doesn't need to map into a higher dimensional space. However, in practice the popular kernel functions (polynomial kernels, rbf kernel, ...) do map into higher dimensions. This is the whole purpose of the kernel trick. | |
| Sep 26, 2014 at 4:10 | comment | added | InformedA | I don't think the kernel function maps input into higher dimensional space. What the kernel function does is mapping input into another space that will be homeomorphic to the original one | |
| Sep 26, 2014 at 1:00 | history | edited | D.W.♦ | CC BY-SA 3.0 |
added 330 characters in body
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| Sep 25, 2014 at 22:55 | history | answered | Aaron | CC BY-SA 3.0 |