Classification Learner and sequentialfs

I use the Classification Learner to select the prediction model that best classifies my data. How can I take advantage of Matlab's sequentialfs to select the best possible features for my data? I tried to export the model, or to export the code generated by the Learner, and then combine the model or the code with sequentiafs with no success so far. BTW, it would be great to add an automatic feature selection option in the next version of the Classification Learner. The manual feature selection is helpful, but sequentialfs seems to automate the whole process, which helps a lot when the number of features is high. Thanks

Answer 1

[Sayan Saha]

Here is an example showing how to use "sequentialfs" with "fitglm" for fitting a logistic model to the data set. Similar steps can be followed for classification with "sequentialfs" as well. You will be performing the classification within the "critfun" function and returning the measure indicating the performance of the classifier.

[Giovanni Barbarossa]

Thank you. I found plenty of examples. This blog is also very useful https://blogs.mathworks.com/loren/2011/11/21/subset-selection-and-regularization/