This shows you the differences between two versions of the page.
Both sides previous revision Previous revision | Next revision Both sides next revision | ||
assignments:assignment4 [2016/09/30 10:23] asa |
assignments:assignment4 [2016/09/30 10:24] asa |
||
---|---|---|---|
Line 5: | Line 5: | ||
Due: October 17th at 11:59pm | Due: October 17th at 11:59pm | ||
- | ===== Part 1: SVM with no bias term ===== | + | ==== Part 1: SVM with no bias term ==== |
Formulate a soft-margin SVM without the bias term, i.e. one where the discriminant function is equal to $\mathbf{w}^{T} \mathbf{x}$. | Formulate a soft-margin SVM without the bias term, i.e. one where the discriminant function is equal to $\mathbf{w}^{T} \mathbf{x}$. | ||
Line 24: | Line 24: | ||
- | ===== Part 3: Soft-margin SVM for separable data ===== | + | ==== Part 3: Soft-margin SVM for separable data ==== |
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 | ||
Line 38: | Line 38: | ||
Is this true or false? Explain! | Is this true or false? Explain! | ||
- | ===== Part 4: Using SVMs ===== | + | ==== Part 4: Using SVMs ==== |
The data for this question comes from a database called SCOP (structural | The data for this question comes from a database called SCOP (structural |