Hi Joao.
There is no build-in way to achieve this.
You can create the kernel matrix of the tensor product of the linear and
the nonlinear kernel explicitly and pass that to SVR.
That will allow the SVR to use both kernels at once.
I think it should just be the product of the two kernel values.
Using different kernels in different regions is not that easily possible.
Hth,
Andy
On 04/10/2014 01:20 PM, João André wrote:
Hi!
I have a question regarding support vectors regression.
Is it possible to develope a kernel that combines the linear and the
rbf kernel, that is, it uses both kernels and applies each one to a
region where each kernel fits better the data?
I thought of this because I was asked to fit this simple, but
discontinuous function, and tried svr but the results were very poor.
Since polynomial expantions are also not a viable solution I thought
that combining a linear + nonlinear kernel would solve this. Any
ideas? Thanks!
Y = f(X) with:
0 <= X <= 0.5 -> Y = 0
0.5 < X < 3.5 -> Y = sin(0.5*(x-0.5)/3)
3.5 <= X <= 4 -> Y = 1
X Y
0 0
0.1 0
0.2 0
0.3 0
0.4 0
0.5 0
0.6 0.052336
0.7 0.104528
0.8 0.156434
0.9 0.207912
1 0.258819
1.1 0.309017
1.2 0.358368
1.3 0.406737
1.4 0.45399
1.5 0.5
1.6 0.544639
1.7 0.587785
1.8 0.62932
1.9 0.669131
2 0.707107
2.1 0.743145
2.2 0.777146
2.3 0.809017
2.4 0.838671
2.5 0.866025
2.6 0.891007
2.7 0.913545
2.8 0.93358
2.9 0.951057
3 0.965926
3.1 0.978148
3.2 0.987688
3.3 0.994522
3.4 0.99863
3.5 1
3.6 1
3.7 1
3.8 1
3.9 1
4 1
--
João André
Engenheiro Civil, Mestre / Civil Engineer, M.Sc.
Bolseiro de Doutoramento / PhD Student
Núcleo de Comportamento de Estruturas / Structural Behaviour Division
Departamento de Estruturas / Structures Department
Laboratório Nacional de Engenharia Civil / National Laboratory for
Civil Engineering
LNEC, Av. Brasil 101, 1700-066 Lisboa / Lisbon, Portugal
Web: http://www.lnec.pt/
E-mail: jan...@lnec.pt <mailto:jan...@lnec.pt>
Telefone / Phone: (+351) 218 443 355
Fax: (+351) 218 443 025
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