Machine Learning/Python question please help

You are given the data set StudySleep.xlsx. Split the data into training / testing sets as before (first 10 points as training, last two as testing). Normalize the data if necessary.

Use the SVM algorithm with soft margins on this data set.

1. Determine the coefficients and the equation of the boundaries (soft and hard margins) for a linear kernel.

i. Make a plot showing your results.

ii. Which support vectors were chosen? Why were these chosen?

2. Plot the boundaries using polynomial, radial basic, and sigmoid kernels. Compare these results including the linear kernel.

StudySleep.xlsx Data:

Study Sleep Score

4 6.5 Fail

6 6 Fail

12 6 Pass

5 6.5 Fail

10 7 Pass

2 7.5 Fail

12 8 Pass

15 8.5 Pass

3 7 Fail

10 7.5 Pass

5 9 Fail

11 7 Pass