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CSCI 1950-F Homework 3:Handwritten Digit ClassificationBrown University, Spring 2012Homework due at 12:00pm on February 23, 2012In this problem set, we consider the problem of handwritten digit recognition. We willuse a subset of the MNIST database, which has become a benchmark for testing a widerange of classification algorithms. Seeif you’d liketo read more about it. The particular version of the data which we’ll use, as well as someuseful Matlab scripts, are available here:/course/cs195f/asgn/hw3_mnist/This code should be used to load and define matrices of training and test data for the variousproblems below.In the MNIST database, each training or test example is a 28-by-28 grayscale image.To ease programming of learning algorithms, these images have been converted to vectorsof length 282= 784 by sorting the pixels in raster scan (row-by-row) order.The Matlabreshapecommand can be used to convert these vectors back to images for visualization.For example, we can plot the third training example of class 1 as follows:>> imagesc(reshape(train1(3,:), 28, 28)’);To reduce computational complexity and simulation time, in the following questions we focuson only three of the ten handwritten digits: “1”, “2”, and “7”.