Instructions- Provide the python code and the mathematical equation.

2.) Perform a polynomial regression using orders 2, 3, 4, and 5 on all the attributes.

E B C D 1 X Y Z Out 2 0.03242 0.974273 0.994142 3 3 0.170399 0.867565 0.883816 9 4 0.286935 0.04752 0.827146 18 5 0.331351 0.819748 0.812681 20 6 0.356502 0.255186 0.77656 32 7 0.377693 0.697032 0.745939 34 8 0.430754 0.57115 0.71584 36 9 0.430906 0.659177 0.690477 55 10 0.493918 0.64866 0.664306 66 11 0.571127 0.62422 0.624368 68 12 0.589867 0.64797 0.569055 72 13 0.721042 0.630403 0.535076 76 14 0.734787 0.079293 0.498173 99 15 0.763741 0.64668 0.361384 102 16 0.834348 0.348698 0.207515 111 17 0.862977 0.810081 0.182405 114 18 0.887153 0.171466 0.169805 116 19 0.898905 0.19058 0.113373 121 20 0.942401 0.827727 0.104913 126 21 0.956432 0.478804 0.012389 131 22 Exercise 2 E B C D 1 X Y Z Out 2 0.03242 0.974273 0.994142 3 3 0.170399 0.867565 0.883816 9 4 0.286935 0.04752 0.827146 18 5 0.331351 0.819748 0.812681 20 6 0.356502 0.255186 0.77656 32 7 0.377693 0.697032 0.745939 34 8 0.430754 0.57115 0.71584 36 9 0.430906 0.659177 0.690477 55 10 0.493918 0.64866 0.664306 66 11 0.571127 0.62422 0.624368 68 12 0.589867 0.64797 0.569055 72 13 0.721042 0.630403 0.535076 76 14 0.734787 0.079293 0.498173 99 15 0.763741 0.64668 0.361384 102 16 0.834348 0.348698 0.207515 111 17 0.862977 0.810081 0.182405 114 18 0.887153 0.171466 0.169805 116 19 0.898905 0.19058 0.113373 121 20 0.942401 0.827727 0.104913 126 21 0.956432 0.478804 0.012389 131 22 Exercise 2