2. [Prompt 2] Consider a dataset with n points and p=4 features which has a covariance matrix, Ex. The eigenvalues of Ex are given by A₁ = X₂ = 3 and A3 = A4 = 1. The associated eigenvectors are: $1 x1 O || 2 1 [1] 2 Using the top two principal components, which is a 2-dimensional reduction of the following data point: 1,42 = √/2 ° [3] 03 = 04 = √/2 0
2. [Prompt 2] Consider a dataset with n points and p=4 features which has a covariance matrix, Ex. The eigenvalues of Ex are given by A₁ = X₂ = 3 and A3 = A4 = 1. The associated eigenvectors are: $1 x1 O || 2 1 [1] 2 Using the top two principal components, which is a 2-dimensional reduction of the following data point: 1,42 = √/2 ° [3] 03 = 04 = √/2 0
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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