Is SVM resilient to noise
3 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Diver
el 9 de Mayo de 2016
Respondida: Image Analyst
el 9 de Mayo de 2016
I have tranning set composed of 36 features. when I calculated "explained" value of PCA using Matlab. I notice that only the first 24 components are important.
My question is, would I gain a better accuracy (prediction) if I omit the reset of the components (the other 12 components). Or SVM is very resilient to noise which means that regardless whether I removed the other 12 components or not. performance will not change that much.
0 comentarios
Respuesta aceptada
Image Analyst
el 9 de Mayo de 2016
I would think it would matter where the noise was. If it's far away from the dividing line, then it doesn't make any difference. If it's close to the dividing line, then yeah, it makes a huge difference.
0 comentarios
Más respuestas (0)
Ver también
Categorías
Más información sobre Dimensionality Reduction and Feature Extraction en Help Center y File Exchange.
Productos
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!