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    Samarth
    This document discusses linear classification and the optimal hyperplane. The optimal hyperplane is found by minimizing WTW subject to constraints involving the weights W, data points X, labels y, and bias b. The Lagrangian is used to solve this constrained optimization problem to find the optimal hyperplane.

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    Untitled Presentation PDF

    Uploaded by

    Samarth
    16 views1 page
    This document discusses linear classification and the optimal hyperplane. The optimal hyperplane is found by minimizing WTW subject to constraints involving the weights W, data points X, labels y, and bias b. The Lagrangian is used to solve this constrained optimization problem to find the optimal hyperplane.

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    This document discusses linear classification and the optimal hyperplane. The optimal hyperplane is found by minimizing WTW subject to constraints involving the weights W, data points X, labels y, and bias b. The Lagrangian is used to solve this constrained optimization problem to find the optimal hyperplane.

    Copyright:

    © All Rights Reserved
    Download as PDF, TXT or read online from Scribd
    Download as pdf or txt
    16 views1 page

    Untitled Presentation PDF

    Uploaded by

    Samarth
    This document discusses linear classification and the optimal hyperplane. The optimal hyperplane is found by minimizing WTW subject to constraints involving the weights W, data points X, labels y, and bias b. The Lagrangian is used to solve this constrained optimization problem to find the optimal hyperplane.

    Copyright:

    © All Rights Reserved
    Download as PDF, TXT or read online from Scribd
    Download as pdf or txt
    of 1

    Case of linear classification(cont.

    )
    ● The optimal hyperplane is a solution of the following
    constrained optimization problem
    Minimize WTW
    Subject to 1-yi(WTXi+b)<=0 ,i=1,...,n
    ● The Lagrangian is given by

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