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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