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Is SVM sensitive to unbalanced observations? The observations in one class is 3-4 times of the observation in an other class in binary classification

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Zeynab Mousavikhamene
Zeynab Mousavikhamene on 19 May 2020
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My first question is sensitivity of SVM to unbalanced datapoints. How much SVM is sensitive to that?
And is there any functionality designed i the fitcsvm to account for the unbalance in the datapoints in binary classification? I know that oversampling the smaller class or undersampling the larger class can be a solution to deal with "unbalanced" observation but I am interested for other approaches.
I checke "prior" and found it's role is only to remove observations with zero prior probablity and apparently doesnot play role in the classification step.

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