Return to Question

Can someone explain me how one goes about designing a SVM decision function? Or point me to resource that discusses a concrete example.

EDIT

For the below example, I can see that the equation $X_2 = 1.5$ separates the classes with maximum margin. But how do I adjust the weights and write equations for hyperplanes in the following form.

$$\begin{array}{ll} H_1 : w_0+w_1x_1+w_2x_2 \ge 1 & \text{for}\; Y_i = +1 \\ H_2 : w_0+w_1x_1+w_2x_2 \le -1 & \text{for}\; Y_i = -1.\end{array} $$

I'm trying to get the underlying theory right in 2-D space (as it's easier to visualize) before I think about higher dimensions.

Can someone explain me how one goes about designing a SVM decision function? Or point me to resource that discusses a concrete example.

EDIT

For the below example, I can see that the equation $X_2 = 1.5$ separates the classes with maximum margin. But how do I adjust the weights and write equations for hyperplanes in the following form.

$$\begin{array}{ll} H_1 : w_0+w_1x_1+w_2x_2 \ge 1 & \text{for}\; Y_i = +1 \\ H_2 : w_0+w_1x_1+w_2x_2 \le -1 & \text{for}\; Y_i = -1.\end{array} $$

I'm trying to get the underlying theory right in 2-D space (as it's easier to visualize) before I think about higher dimensions.

I have worked out solution for this Can someone please confirm if this is correct?

weight vector is (0,-2) and W_0 is 3

$$\begin{array}{ll} H_1 : 3+0x_1-2x_2 \ge 1 & \text{for}\; Y_i = +1 \\ H_2 : 3+0x_1 -2x_2 \le -1 & \text{for}\; Y_i = -1.\end{array} $$

Can someone explain me how one goes about designing a SVM decision function? Or point me to resource that discusses a concrete example.

EDIT

For the below example, I can see that the equation X2 = 1.5 separates the classes with maximum margin. But how do I adjust the weights and write equations for hyperplanes in the following form.

$$H1 : w0+w1x1+w2x2 >= 1 for Yi = +1 $$ $$H2 : w0+w1x1+w2x2 <=-1 for Yi = -1: $$

I'm trying to get the underlying theory right in 2-D space (as it's easier to visualize) before I think about higher dimensions.

Can someone explain me how one goes about designing a SVM decision function? Or point me to resource that discusses a concrete example.

EDIT

For the below example, I can see that the equation $X_2 = 1.5$ separates the classes with maximum margin. But how do I adjust the weights and write equations for hyperplanes in the following form.

$$\begin{array}{ll} H_1 : w_0+w_1x_1+w_2x_2 \ge 1 & \text{for}\; Y_i = +1 \\ H_2 : w_0+w_1x_1+w_2x_2 \le -1 & \text{for}\; Y_i = -1.\end{array} $$

I'm trying to get the underlying theory right in 2-D space (as it's easier to visualize) before I think about higher dimensions.

Can someone explain me how one goes about designing a SVM decision function? Or point me to resource that discusses a concrete example.

Can someone explain me how one goes about designing a SVM decision function? Or point me to resource that discusses a concrete example.

EDIT

For the below example, I can see that the equation X2 = 1.5 separates the classes with maximum margin. But how do I adjust the weights and write equations for hyperplanes in the following form.

$$H1 : w0+w1x1+w2x2 >= 1 for Yi = +1 $$ $$H2 : w0+w1x1+w2x2 <=-1 for Yi = -1: $$

I'm trying to get the underlying theory right in 2-D space (as it's easier to visualize) before I think about higher dimensions.