Consider the following dataset of 3 features namely X, Y, and Z. Determine the principal components and select the necessary components so that the transformed dataset holds 95% of the normalized cumulative variances. X Y Z Instance 1: -2 0 -2 Instance 2: 0 2 2 Instance 3: 2 -2 0 Note that you have the transform the eigenvectors to unit vectors before forming the feature vector i.e., you have to determine the eigenvectors Xi Xi+1 Хп and afterward, each of the eigenvectors must be scaled to unit length xi eigenvector x1+1 using the equation x¿ Xi = Where, ||x||2 is the 12 ||X||2 , x'n norm of vector x=[xi, Xi+1, ... xn].
Consider the following dataset of 3 features namely X, Y, and Z. Determine the principal components and select the necessary components so that the transformed dataset holds 95% of the normalized cumulative variances. X Y Z Instance 1: -2 0 -2 Instance 2: 0 2 2 Instance 3: 2 -2 0 Note that you have the transform the eigenvectors to unit vectors before forming the feature vector i.e., you have to determine the eigenvectors Xi Xi+1 Хп and afterward, each of the eigenvectors must be scaled to unit length xi eigenvector x1+1 using the equation x¿ Xi = Where, ||x||2 is the 12 ||X||2 , x'n norm of vector x=[xi, Xi+1, ... xn].
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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This is a mathmetical problem. You have to do the full math and not use
![Consider the following dataset of 3 features namely X, Y, and Z. Determine
the principal components and select the necessary components so that the
transformed dataset holds 95% of the normalized cumulative variances.
X
Y
Z
Instance 1:
-2
0
-2
Instance 2:
0
2
2
Instance 3:
2
-2
0
Note that you have the transform the eigenvectors to unit vectors before
forming the feature vector i.e., you have to determine the eigenvectors
Xi
Xi+1
Хп
and afterward, each of the eigenvectors must be scaled to unit length
xi
eigenvector x1+1 using the equation x¿
Xi
=
Where, ||x||2 is the 12
||X||2
,
x'n
norm of vector x=[xi, Xi+1,
...
xn].](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc223e699-5e91-4076-9e8c-8f74eecce0ff%2F36451649-bf27-4a01-9340-4cd4895ede53%2Fgx0n0q9_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Consider the following dataset of 3 features namely X, Y, and Z. Determine
the principal components and select the necessary components so that the
transformed dataset holds 95% of the normalized cumulative variances.
X
Y
Z
Instance 1:
-2
0
-2
Instance 2:
0
2
2
Instance 3:
2
-2
0
Note that you have the transform the eigenvectors to unit vectors before
forming the feature vector i.e., you have to determine the eigenvectors
Xi
Xi+1
Хп
and afterward, each of the eigenvectors must be scaled to unit length
xi
eigenvector x1+1 using the equation x¿
Xi
=
Where, ||x||2 is the 12
||X||2
,
x'n
norm of vector x=[xi, Xi+1,
...
xn].
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