I have a dataset that is heavily skewed in one class. The training with support vector machine (SVM), by either fitcsvm.m or fitcecoc.m, cannot give desirable results. The accuracy for the class that has more samples is more than 90%, but for the class with much fewer samples is barely 70%. Is there any way to improve the training by SVM? or other methods that can be used to tackle the umbablanced data training?
MATLAB: How to deal with imbalanced dataset classification by support vector machine
imbalanced data support vector machine
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