Hard Svm Is The Learning Rule In Which Return An Erm Hyperplane #364
Hard SVM is the learning rule in which return an ERM hyperplane that separates the training set with the largest possible margin.
This multiple choice question (MCQ) is related to the book/course
gs gs126 Neural Networks.
It can also be found in
gs gs126 Support Vector Machines - Margin and Hard SVM - Quiz No.1.
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