ECS 172 Term Project

Important dates

• Progress report: Due Monday, March 14, 11:59 pm, in the form of an e-mail message to me. Must be a frank discussion stating the contribution of each group member so far.
• Submission: Scheduled final exam day (no written final), Wednesday, March 16, 2022, 11:59 pm. NO LATE SUBMISSIONS.

Problem A

This is a mini (nano) research project, in which you will investigate the effects of three general parameters on accuracy and run time of collaborative filtering methods.

• n: Number of users.
• m: Number of items.
• d: Density = number of non-NA values / nm.

You will hold every pair of these variables fixed while varying the third.

A suggestion: For some selected dataset, first find the estimated ratings matrix aEst. Then reduce n, m and d by thinning it out, replacing some values by NAs. You may find rectools::toUserItemRatings() handy here; given an A matrix, it produces the input data frame in (userID, itemID, rating) form. Running toUserItemRatings() on aEst will thus produce a fake data frame of this form, on which you can run the various rec sys models.

Note: To fix m and d, for instance, take only the first m columns (or randomly chosen m columns) from aEst. Then randomly sprinkle a proportion 1-d of NAs in what remains.

Your report should have lots of graphs, e.g. MAPE accuracy plotted against n, for m and d fixed. You may wish to draw sevral curves in each plot. The code used to generate them must be in R, and supplied with your submission package. I suggest either ggplot2 or lattice. I personally find the colors more vivid in the latter, but the former has the possible advantage of many add-on packages.

Your report must explain in detail what you did, why you did it, and the conclusions you drew from it.

Choice of datasets and collaborative filtering methods is up to you, but the latter should consist of at least one matrix-factorization (MF) method and one non-MF.

Important General Rules

PLEASE FOLLOW THESE RULES 100%!

• Don't skimp on time devoted to the writing. The phrasing matters! This is true both in terms of having good, professional writing quality, but also in terms of proper interpretation, which will be vital in your report.
• You must use LaTeX and R throughout.
• Submit your report, including all files, i.e. .tex, .pdf, R code (see below), any image files, etc., to my handin site on CSIF (NOT the TAs' sites), username matloff, directory 172project. Be SURE to do a ``practice run'' well before the deadline, so you are sure you know how the procedure works (each submission will overwrite the last).
• Your LaTeX file must be named ProjectReport.tex, and the corresponding PDF ProjectReport.pdf. The grading script will look for these; don't disappoint the grading script!
• The name of your submitted file must be of the form email1.email2....tar , where each emaili is the UCD e-mail address of group member i, e.g. bclinton.gwbush.bobama.dtrump.tar. Note the periods separating fields. Don't get the address wrong! Otherwise the grading script may not give someone credit.
• Your .tar file must contain only regular files, NO SUBDIRECTORIES!!!! And .tar does NOT mean .tar.gz or .tar.bz2 (or for that matter .rar, which one student used once). The grading script will execute

  tar xf youraddresses.tar  # unpack
  ls ProjectReport.tex ProjectReport.pdf  # check for proper files
  xpdf ProjectReport.pdf  # view PDF
  

  Note that the script will NOT do cd.

• Place all your code in a file TermProject.R, as well as in an Appendix to your report (LaTeX \appendix \section{}). I may execute your code, so make sure it is runnable.
• Absolutely NO late reports will be accepted. As you near the deadline, keep submitting what you have (each one will overwrite the last), so that at least you will get a lot of credit even if you don't finish.
• Include a section listing each team member's contribution to the project -- who did what. If a member did not participate, do not include him/her in this section, nor in the .tar file name. Don't forget this section!
• DOUBLE-CHECK THAT YOU ARE MEETING ALL SPECS! Whoever does the actual turning in of your submission, impress upon him/her that this is a huge responsiblity that can affect everyone's grade.

Grading

General commnets:

• Groups that put in a reasonable amount of time -- and thought! -- almost always receive an A or A+ grade on the project. Groups that do not complete the project usually get a D grade. PLEASE START EARLY!
• As explained in class, groups that do good work on the project receive an extra bonus in their course grades, beyond what your quiz and homework grades are. The boost is always at least one notch (e.g. B to B+) and typically two notches (e.g. B to A-). E.g. a student could have strictly B work in the homework and quizzes and yet still get an A- in the course.
• A+ grades are very possible, and can have a significant impact on your course grade, letters of recommendation, knighthoods, marriage prospects, coronations, etc.

Criteria:

• Technical content of the work (correctness, thoroughness etc.).
• Adherence to instructions.
• Professional quality of the work: Clear, engaging writing, using correct grammar; it need not (should not) be pretentious, but avoid being too colloquial ("the mean was kinda low"). Presentation need not be fancy, but graphs and tables should be used where helpful.