4. PC with images. A dataset has 1000 images of size 28 x 28, represented as python array x with shape (100, 28, 28). You are given the following python functions: Y = reshape (X, shape) # Reshapes X to a shape pca = PCA(n.components = nc) # Creates a PCA object pca.fit(Y) # Finds the mean and PCs from training data Y z = pca.transform(Y) Yhat = pca.inverse.transform(Z) # Invert the PC transform # Find coefficients in the PC basis Write a few lines of python code to (i) fit a PC model from the first 500 images with 5 components; and (ii) create an array of approximations of the remaining 500 images.
4. PC with images. A dataset has 1000 images of size 28 x 28, represented as python array x with shape (100, 28, 28). You are given the following python functions: Y = reshape (X, shape) # Reshapes X to a shape pca = PCA(n.components = nc) # Creates a PCA object pca.fit(Y) # Finds the mean and PCs from training data Y z = pca.transform(Y) Yhat = pca.inverse.transform(Z) # Invert the PC transform # Find coefficients in the PC basis Write a few lines of python code to (i) fit a PC model from the first 500 images with 5 components; and (ii) create an array of approximations of the remaining 500 images.
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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
Transcribed Image Text:4. PC with images. A dataset has 1000 images of size 28 x 28, represented as python array x
with shape (1000, 28 , 28). You are given the following python functions:
Y = reshape (X, shape)
рса %3D РCА(n-components
# Reshapes X to a shape
nc)
# Creates a PCA object
рса. fit(Y)
# Finds the mean and PCs from training data Y
Z = pca.transform (Y)
= pca.inversc.transform (Z)
# Find coefficients in the PC basis
Yhat
# Invert the PC transform
Write a few lines of python code to (i) fit a PC model from the first 500 images with 5
components; and (ii) create an array of approximations of the remaining 500 images.
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