Week 3 (June 10 – June 16) Progress

Added the loss, resubpredict, resubloss, resubmargin method to the classdef ClassificationSVM.

This week, I added the loss, resubpredict, resubloss, resubmargin method. I used the following resources:

  • Libsvm PDF by CSIE: This document contains the mathematical formulations implemented in LIBSVM, which I will use to cross-check against MATLAB's documentation.
  • README provided with the LIBSVM package for MATLAB/Octave.
  • Matlab's Documentation: resubpredict, resubloss, resubmargin

On June 11, 2024, I had a meeting with Andreas. The following points were discussed:

  • I discussed the printf problem of the svmtrain function. Andreas advised me not to worry about it now as he plans to update the svmtrain and svmpredict functions in the coming months, and we can address this issue towards the end of the GSoC period.
  • MATLAB's ClassificationSVM Supports only binary or one-class SVM. However, my classdef supports multi-class SVM as well. The methods (like margin, loss) of the classdef will support only binary class SVM models as inputs and will give a warning message for multi-class models.
  • Writing mathematical functions in the help doc using Latex notation by using the @tex tag.

Now, I will start working on the crossval method. I will be using the following resources:

  • Libsvm PDF by CSIE: This document contains the mathematical formulations implemented in LIBSVM, which I will use to cross-check against MATLAB's documentation.
  • README provided with the LIBSVM package for MATLAB/Octave.
  • Matlab's Documentation on the crossval  method.
Next meeting will be on June 25, 2024.

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