清空筛选条件
清空筛选条件

SVM classification with different kernels

6 次查看（过去 30 天）
caterina
caterina 2012-12-27
评论： Jeremy Huard 2023-1-31
I am using an SVM (SVM_train, Bioinformatics toolbox) to classify data, and I would like to have my final trained SVM models with different kernel functions. I didn't understand how to specify my own kernel maps: if I would like to use a Cauchy kernel defined as
k=(1/(1+(|u-v|^2/sigma))
where u,v are the vectors of the X data, and sigma is the parameter defined by the user (sigma=2.5). How I have to edit this matlab statement?
svmStruct = svmtrain(X,group,'Kernel_Function', 'rbf','RBF_Sigma', 2.5, 'Method', 'QP');
Thank you!
  1 个评论
Jeremy Huard
Jeremy Huard 2023-1-31
Users using R2014b or newer should use the fitcsvm function for for one-class and binary classification or fitcecoc for multiclass classification instead.
There you can specify a custom kernel function by adding the 'KernelFunction','myfunction' name-value pair, where myfunction is the name of your function containing the kernel function definition.

请先登录，再进行评论。

请先登录，再回答此问题。

回答（4 个）

Ilya
Ilya 2012-12-27
caterina
caterina 2012-12-28
Hi Ilya anche thank you for you answer. I read it that thread before writing and still I did not understand what it is wrong in my code. I created my kernel code that I saved in a folder 'pgm_qkda'. You can find the code below
clear all
clc;
addpath('/Users/Documents/Parallels/shared/D/KQDA/matlab2/pgm_qda');
x=[3 3 4 5 6 7 8 0.1 0.2
3 4 3 5 7 7 5 0.5 0.6
7 7 2 3 3 4 5 0.4 0.5
3 3 4 5 6 2 6 0.2 0.3];
group=[1,1, 2, 2]';
p1=2.5;
svmStruct = svmtrain(x,group,'Kernel_Function', @(u,v) kfun(u,v,p1), 'Method', 'QP');
The kfun function is defined as:
function kval = kfun(u,v,p1);
dot=((u-v)*(u-v)')/p1;
kval = 1/(1+dot);
Matlab gives me a warning message: Error using ==> svmtrain at 453 Error calculating the kernel function: Matrix dimensions must agree.
I do not understand where is my mistake. If you can help me I really appreciate.
  2 个评论
Ilya
Ilya 2012-12-28
Replace
kval = 1/(1+dot);
with
kval = 1./(1+dot);
./ is for elementwise division. / is for matrix division.
Also, please do not post follow-up questions as answers to your own posts. Use comments for that.
Fourth Sem Geethanjali Electrical and Electronics Engineering
Fourth Sem Geethanjali Electrical and Electronics Engineering 2020-12-7
hi
svmStruct = svmtrain(x,group,'Kernel_Function', @(u,v) kfun(u,v,p1), 'Method', 'QP');
how will the function call change if i use fitcsvm instead of svmtrain.
can you please help me.

请先登录，再进行评论。

Sandy
Sandy 2014-10-3
Hi Caterina,
Just want to check whether you are able to rectify tha above issues. I am also getting the same error. Will you post me the code for above custom kernel.
Thanks in advance.
muqdad aljuboori
muqdad aljuboori 2017-4-2
Hi I very interested in this discussion I tried to apply the new funcion in my project but it doesnt work that what i did
SVR1 = fitrsvm(TrainInputs,TrainTargets,...
'KernelFunction', @(u,v) kfun3(u,v) ,...
'KernelScale','auto','Standardize',true);__
and the error is
Error using classreg.learning.modelparams.SVMParams.make (line 225) You must pass 'KernelFunction' as a character vector.
Error in classreg.learning.FitTemplate/fillIfNeeded (line 598) this.MakeModelParams(this.Type,this.MakeModelInputArgs{:});
Error in classreg.learning.FitTemplate.make (line 124) temp = fillIfNeeded(temp,type);
any suggestion ??? thanks
  1 个评论
Jeremy Huard
Jeremy Huard 2023-1-31
You should specify the kernel function as char array:
SVR1 = fitrsvm(TrainInputs,TrainTargets,...
'KernelFunction', 'kfun3',...
'KernelScale','auto','Standardize',true);

请先登录，再进行评论。

类别

在 Help Center 和 File Exchange 中查找有关 Get Started with Statistics and Machine Learning Toolbox 的更多信息

标签

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by