讲解：CSE 404、Data、c/c++、Java，PythonDatabase|Processing

CSE 404: Introduction to Machine Learning (Spring 2020)Homework #6Due 3/12/2020Note: LFD refers to the textbook “Learning from Data”.1. (5 points) Exercise 3.6 (page 92) in LFD.2. (5 points) Exercise 3.7 (page 92) in LFD.3. (15 points) Handwritten Digits Data: You should download the two data files with handwrittendigits data: training data (ZipDigits.train) and test data (ZipDigits.test). Each row is adata example. The first entry is the digit, and the next 256 are grayscale values between -1and 1. The 256 pixels correspond to a 16 × 16 image. For this problem, we will only use the1 and 5 digits, so remove the other digits from your training and test examples.(a) (5 points) Familiarize yourself with the data by giving a plot of two of the digit images.(b) (5 points) Develop two features to measure properties of the image that would be usefulin distinguishing between 1 and 5. You may use symmetry and代写CSE 404作业、代做Data留学生作业、代做c/c++编程设计作业、代写Java，Python作业 代写Data average intensity (asdiscussed in class).(c) (5 points) As in the text, give a 2-D scatter plot of your features: for each data example,plot the two features with a red × if it is a 5 and a blue ◦ if it is a 1.4. (40 points) Classifying Handwritten Digits: 1 vs. 5. Implement logistic regression for classifi-cation using gradient descent to find the best separator that you can using the training dataonly. Use your 2 features from the above question (3b) as the input. The output is +1 if theexample is a 1 and -1 if the example is a 5.(a) (10 points) Give separate plots of the training and test data, together with the separators.(b) (10 points) Compute Ein on your training data and Etest, the test error on the test data.(c) (10 points) Now repeat (b) using a 3rd order polynomial transform.(d) (10 points) Would you use the linear model with or without the 3rd order polynomialtransform? Explain.1转自：http://www.daixie0.com/contents/9/4870.html