kernel scale in svm ?
16 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
M. A.hsh
el 15 de Oct. de 2025 a las 17:01
Comentada: M. A.hsh
el 15 de Oct. de 2025 a las 17:37
In:
template = templateSVM(...
'KernelFunction', 'gaussian', ...
'KernelScale', 3.9, ...
'BoxConstraint', 1, ...
'Standardize', true);
modelSVM = fitcecoc(...
predictors, respones, ...
'Learners', template, ...
'Coding', 'onevsone');
Kernel scale here: represents gamma or sigma ?
0 comentarios
Respuestas (1)
Walter Roberson
el 15 de Oct. de 2025 a las 17:24
According to https://www.mathworks.com/matlabcentral/answers/516738-what-kernel-scale-in-svm-really-is#comment_983291
@Hiro Yoshino wrote
Kernelscale is literally a scaling parameter for the input data.
The input data is recommended to be scaled with respect to a feature before being applied to the Kernel function. When the absolute values of some features range widely or can be large, their inner product can be dominant in the Kernel calculation. So this kernelScale can be used to prevent this from happening. It also helps maintain the information.
Ver también
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!