For the separable data with D-dimensional feature vectors, K classes, and a total of N examples, how many unknown variables are to be estimated in SVM training to get a separating plane ‘which maximizes margin? How many constraints?
A)D variables, N constraints
B)(D+1) variables, N constraints
C)D variables, K constraints
D)(D+1) Variables, K constraints
Answer:B
For the separable data with D-dimensional feature vectors, K classes, and a total of N examples, how many unknown variables are to be estimated in SVM training to get a separating plane ‘which maximizes margin? How many constraints?
A)D variables, N constraints B)(D+1) variables, N constraints C)D variables, K constraints D)(D+1) Variables, K constraints