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Step 4. Kernel regression The weights , are estimated by minimizing s regularized mean square error: min () - /(x:w)) + bw Kw. i= where

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Step 4. Kernel regression The weights , are estimated by minimizing s regularized mean square error: min () - /(x:w)) + bw Kw. i= where W is the column vector formed by w= [w/], and K is the kernel matrix. . Please derive the optimal solution of w using matrix inverseion (no need to show the work) Complete the following function to implement the calculation of W

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