PS5

Welcome to PS5 for CS 320! This homework assignment has 2 parts: Decision Trees and Unsupervised Learning. The Decision Trees notebook is available now; the Unsupervised Learning notebook will be available on Monday.

Assignment logistics

This is a partner assignment, which means you should complete all pieces of the homework with your assigned partner (same partner as previous assignment). (Note that this means you should complete the assignment together. You should not divide-and-conquer.)

Collaboration and academic honesty

You can talk to others in the class about general problem solving strategies, but you should not share code, writing, or specific insights with people other than your partner. The standard class academic honesty policies apply (see the syllabus for more details, but the tldr is that you can freely use (with citation) documentation or materials on Moodle, you can use other static online material with caution, and you cannot use generative AI.) As always, reach out to Anna with and questions about collaboration or AI usage.

Setup

Download the starter files here. Then, upload the starter code to Google Drive. Like in PS4, you'll complete each of the notebooks in Colab.

Part 1: Decision trees

In ps5-nb1-decision-trees.ipynb, you'll create decision tree and random forest models.

Part 2: Unsupervised learning

In ps5-nb2-unsupervised.ipynb, you'll answer math/conceptual questions about clustering (and perhaps also dimensionality reduction).

Handing in the assignment

To prepare your submission, open collect_submission.ipynb in Colab and follow the instructions there.

Make sure that only one person in each partnership submits to Gradescope (after submitting, you can add the other partner as a group member).

Grading

Each notebook in this homework will be weighted equally. Each sub-problem will be graded out of 4 points, where 4 indicates mastery, 3 proficency, 2 significant progress, and 1 minimal progress. Your grade for each notebook will be the average of your score on each of its subparts. See Moodle for more details on homework grading.

Tips

  • Make sure to save your work!
  • If you use any images in Part 2, double check that they show up in the PDF you are submitting to Gradescope.
  • If your kernel is disconnected (e.g., if you take a break from working), you will need to re-run all previous cells
  • Please make sure you've run each notebook, in order, before submitting. I should be able to see all of the cell outputs, and if I rerun the whole notebook, I should see exactly the same cell outputs as what you submit.