Hello community,
I am trying to compare different feature selection methods on my own big set of data (10 classes) which I want to train with support vector machines and it works very well so far with filter methods and wrapped methods. Now I want to use L1-Regularization as a feature selection. I am training my data pretty straight forward for now just to try it out before optimizing stuff:
t=templateLinear('Regularization','lasso');
model=fitcecoc(X,Y,'Learners',t);
This works fine. But I am wondering how to find out the preferred features and I have no clue…
I looked at all the parameters of the model and of all the binarymodels themself, but I don't really find any coefficients that seem to make sense for what I am looking for. Probably my fault, but I hope somebody can help me!
Thank you very much!
Jojo 🙂
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