Support Vector Machines

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01. Intro
02. Which line is better?
03. Minimizing Distances
04. Error Function Intuition
05. Perceptron Algorithm
06. Classification Error
07. Margin Error
08. (Optional) Margin Error Calculation
09. Error Function
10. The C Parameter
11. Polynomial Kernel 1
12. Polynomial Kernel 2
13. Polynomial Kernel 3
14. RBF Kernel 1
15. RBF Kernel 2
16. RBF Kernel 3
17. SVMs in sklearn
18. Recap & Additional Resources

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12. Polynomial Kernel 2

SVM 10 Polynomial Kernel 2 V2

Function quiz

Which equation could come to our rescue?

x + y

xy

x^2 + y^2

SOLUTION:

x^2 + y^2

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