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Regression Model Report

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Added on  2023-04-10

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This report discusses the variables and model capacity for an insurance firm using regression analysis. It explains the relationship between independent and dependent variables and the types of regression models. The report also covers the training, validation, under-fitting and over-fitting, and generalization error in the model.

Regression Model Report

   Added on 2023-04-10

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Machine Learning
Student Name
Institution
State
1. Let,
S= [ cos α sin α
sin α cos α ]
a. Orthogonal matrix is a matrix such
that; S ST =I where I is the identity
matrix.
Let α be 300
S= [ cos 30 sin 30
sin 30 cos 30 ]= [ 0.866 0.5
0.5 0.866 ]
S ST =
[0.866 0.5
0.5 0.866 ][0.866 0.5
0.5 0.866 ]
S ST =[ 0.5 0
0 0.5 ]
S ST =0.5 [1 0
0 1 ]
Since we can easily get identity matrix,
matrix S is orthogonal
b. 2 X 2 Symmetric matrix
A=
[a11 a12
a21 a22 ]
Let A=
[ 4 3
3 2 ]
tan 2 α =6
2 =3
2 α=tan1 3
2 α=71.5 60
α =35.7 80
B=¿
[ cos 35.78 sin35.78
sin 35.78 cos 35.78 ][4 3
3 2 ][cos 35.78 sin35.78
sin 35.78 cos 35.78 ]
B=¿ [ 0.81 0.58
0.58 0.81 ][ 4 3
3 2 ][ 0.81 0.58
0.58 0.81 ]
B= [ 4.98 3.59
0.11 0.12 ][ 0.81 0.58
0.58 0.81 ] =
[ 6.12 0.0
0.0 0.13 ]
Regression Model Report_1

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