Gradiance Online Accelerated Learning
04/02/18, 12)48 PM
Gradiance Online Accelerated Learning Homework Assignment Submitted Successfully.
Devyani • Home Page • Assignments Due • Progress Report
You obtained a score of 0.0 points, out of a possible 9.0 points. You did not answer any questions correctly. You have answered 3 questions incorrectly. Note that the minimum score obtainable is zero points.
• Handouts • Tutorials • Homeworks
Submission number: Submission certificate: Submission time:
165164 BF655421 2018-02-03 23:17:27 PST (GMT - 8:00)
• Lab Projects • Log Out Help
Number of questions: Positive points per question: Negative points per question: Your score:
3 3.0 1.0 0
Gradiance quiz on Recommender Systems. You can attempt to answer the questions as many times as you like. Questions get randomly regenerated each time. The score of the *last* submission gets saved into our records (that is, once you get a perfect score, don't submit again with a bad one).
1. Here is a table of 1-5 star ratings for five movies (M, N, P. Q. R) by three raters (A, B, C). M A1 B 2 C5
N 2 3 5
P 3 2 5
Q 4 5 3
R 5 3 2
Normalize the ratings by subtracting the average for each row and then subtracting the average for each column in the resulting table. Then, identify the true statement about the normalized table. a) The entry (A,Q) is -3. b) The smallest element is (A,M). c) The largest element is (C,M). d) The smallest element is (C,R). Answer submitted: b) Your answer is incorrect. Start by averaging each row. For example, the average in the row for C is 4. Then, subtract the average for a row from every element in that row. For example, substract 4 from every element of the last row. Then, you must do the same for columns, in the matrix that results from normalizing the rows. http://www.newgradiance.com/cru/servlet/COTC
Page 1 of 3
Gradiance Online Accelerated Learning
04/02/18, 12)48 PM
2. Below is a utility matrix representing ratings by s A, B, and C for items a through h. ab c d e f A45 5 1 B 3 43 12 C2 13 4
gh 32 1 53
Treat ratings of 3, 4, and 5 as 1 and 1, 2, and blank as 0. Compute the Jaccard distance between each pair of items. Then, cluster the items hierarchically into four clusters, using the Jaccard distance. When a cluster consists of more than one item, take the distance between clusters to be the minimum over all pairs of items, one from each cluster, of the Jaccard distance between those items. Break ties lexicographically. That is, sort the items that would be merged alphabetically, and merge those clusters whose resulting set would be first alphabetically. Then, identify one of the resulting clusters in the list below. a) {b,d,g} b) {d,g} c) {c} d) {a,b,c,d} Answer submitted: d) Your answer is incorrect. Hint: start by replacing 3,4, and 5 by 1 and 1, 2, and blank by 0. Each column is a set -- those rows in which it has a 1. For example, column b is the set {A,B} and column g is {A,C}. Next, compute the Jaccard distance between each pair of columns. For example, the Jaccard distance between b and g is 1 minus the Jaccard simlarity of {A,B} and {A,C}. The similarity is 1/3, because the size of the intersection is 1 and the size of the union is 3. Start the clustering by merging the pair of items with the smallest distance (greatest similarity).
3. Below is a table giving the profile of three items. A101012 B 110016 C010102 The first five attributes are Boolean, and the last is an integer "rating." Assume that the scale factor for the rating is α. Compute, as a function of α, the cosine distances between each pair of profiles. For each of α = 0, 0.5, 1, and 2, determine the cosine of the angle between each pair of vectors. Which of the following is FALSE? a) For α = 2, B is closer to C than A is. b) For α = 2, C is closer to B than A is. c) For α = 1, C is closer to B than A is. d) For α = 2, A is closer to C than B is. Answer submitted: a)
http://www.newgradiance.com/cru/servlet/COTC
Page 2 of 3
Gradiance Online Accelerated Learning
04/02/18, 12)48 PM
Your answer is incorrect. Hint: After computing the dot products of the vectors, with α mutiplying the last component, compute the lengths of the vectors, also as a function of α. For example, |C| = sqrt(2 + 4α2). The cosine of the angle between vectors is their dot product divided by the lengths of both vectors.
Copyright © 2007-2015 Gradiance Corporation.
http://www.newgradiance.com/cru/servlet/COTC
Page 3 of 3