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Pluviophile
Pluviophile
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The optimization goal of the SVMSVM is to maximize the distance between the positive and negative hyperplanes. But before optimizing, how does sklearn first find the positive and negative support vectors and therefore the margin hyperplanes?

The optimization goal of the SVM is to maximize the distance between the positive and negative hyperplanes. But before optimizing, how sklearn first find the positive and negative support vectors and therefore the margin hyperplanes?

The optimization goal of the SVM is to maximize the distance between the positive and negative hyperplanes. But before optimizing, how does sklearn first find the positive and negative support vectors and therefore the margin hyperplanes?

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user3363813
user3363813
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How sklearn SVM find the initial hyperplane before Optimisation?

The optimization goal of the SVM is to maximize the distance between the positive and negative hyperplanes. But before optimizing, how sklearn first find the positive and negative support vectors and therefore the margin hyperplanes?