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Part V Support Vector Machines

Part V Support Vector Machines

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We’ll also see kernels, which give a way to apply SVMs e ciently in very high dimensional (such as in nite-dimensional) feature spaces, and nally, we’ll close o the story with the SMO algorithm, which gives an e cient implementation of SVMs. 1 Margins: Intuition

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