hw3 - CSCI 1950-F Homework 3 Handwritten Digit Classication Brown University Spring 2012 Homework due at 12:00pm on In this problem set we consider the

# hw3 - CSCI 1950-F Homework 3 Handwritten Digit Classication...

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CSCI 1950-F Homework 3: Handwritten Digit Classification Brown University, Spring 2012 Homework due at 12:00pm on February 23, 2012 In this problem set, we consider the problem of handwritten digit recognition. We will use a subset of the MNIST database, which has become a benchmark for testing a wide range of classification algorithms. See if you’d like to read more about it. The particular version of the data which we’ll use, as well as some useful 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 various problems 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 vectors of length 28 2 = 784 by sorting the pixels in raster scan (row-by-row) order. The Matlab reshape command 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 focus on only three of the ten handwritten digits: “1”, “2”, and “7”.