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Problem 2.............................................................................................................................................1
Solution.............................................................................................................................................1
Problem 3.............................................................................................................................................2
Part 1....................................................................................................................................................2
Part 2....................................................................................................................................................4
Problem 2
Solution
The initial stage of the dataset can be used for the specified range, which can access
on (x1, y1) as follows and find the problem models as,
yi iidN (xi
T w , σ2)
It can consider the approximate data values on the dataset, which is given as,
wRR =(λI + xT x)1 xT y
Consider the data on points f(x, y), which can be used for the regression function and find
the values of minimizing square of the sum errors, and W is the parameter.
We can consider the set of dataset(x1, y1) ...... (Xi, yi). The dataset can be used to find the
values of least square on the sum of minimization errors.
The measurement of the dataset can be used for considering the linear relationship of the
response xi, yi.
Yi=W0+
i=1
n
xi
T w +Si
At the same time, it can calculate the minimization of vector and values of matrices.
L=
i
n

i=1
n
xi
T w
Xi=
x 1
x 2
... .. xn
=
The finding linear regression values can be used for the intercept and the vector elements of
the matrix values s X.
Δ wl=
i=1
0
¿ ¿ ¿+w)
Later, it is possible to calculate the values of w on the distribution solution i.e.,
1

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