assignments:assignment4

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assignments:assignment4 [2016/10/03 10:00] asa [Part 2: leave-one-out error for linearly separable data] |
assignments:assignment4 [2016/10/05 11:44] asa [Part 3: Soft-margin SVM for separable data] |
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Suppose you are given a linearly separable dataset, and you are training the soft-margin SVM, which uses slack variables with the soft-margin constant $C$ set | Suppose you are given a linearly separable dataset, and you are training the soft-margin SVM, which uses slack variables with the soft-margin constant $C$ set | ||

- | with the soft margin constant $C$ set | ||

to some positive value. | to some positive value. | ||

Consider the following statement: | Consider the following statement: | ||

- | Since increasing the $\xi_i$ can only increase the objective of the primal problem (which | + | Since increasing the $\xi_i$ can only increase the cost function of the primal problem (which |

- | we are trying to minimize), at the optimal solution to the primal problem, all the | + | we are trying to minimize), at the solution to the primal problem, i.e. the hyperplane that minimizes the primal cost function, all the |

training examples will have $\xi_i$ equal | training examples will have $\xi_i$ equal | ||

to zero. | to zero. |

assignments/assignment4.txt · Last modified: 2016/10/11 18:16 by asa

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