how to classify with svm

1 visualización (últimos 30 días)
Fardin Gorgini
Fardin Gorgini el 28 de En. de 2018
Respondida: Bernhard Suhm el 1 de Feb. de 2018
HI
I have a number of photos that I have featured, that is, 11 properties for each photo. The number of photos is 770. I saved the data to an Excel file, which is 11 * 770.
How should I read this file?
And how do I train an SVM model using these features with svm (rbf, mlp, lvq)?
For svm, I need to take input from the Excel file.
Please help me soon.
  1 comentario
Image Analyst
Image Analyst el 28 de En. de 2018
To read the file you can use readtable(). Then follow the examples with the SVM. For example, you might try the "Classification Learner" app on the Apps tab of the tool ribbon. Attach your Excel workbook if you need more help and maybe someone will try something.

Iniciar sesión para comentar.

Respuestas (1)

Bernhard Suhm
Bernhard Suhm el 1 de Feb. de 2018
The table needs to have the various observations as rows. Alternatively to the ClassificationLearnerApp, you can train an SVM using the fitcsvm() function.
You can switch to a different kernel using the 'KernelFunction' input argument, for RBF it would be 'rbf'.
See https://www.mathworks.com/help/stats/fitcsvm.html for more details.

Community Treasure Hunt

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

Start Hunting!

Translated by