Fall 2021 - STAT207
Data Science Exploration

Lab 11: Classifier Models

Overview

In this eleventh lab, we will use training and test datasets as well as the Log Likelihood Ratio test to help us select explanatory variables to put in a logistic regression model that will be good at predicting observations in new datasets.

Source Branch: lab_11
Due Date: Committed and pushed to git before Tuesday November 9 at 11:59pm CST


Complete the “lab_11” Notebooks (Individual and Group)

Part a: Fetching the Lab Assignment from the Class Respository

Using your command line, navigate to your stat207 repository (cd Desktop -> cd stat207 -> cd NETID), replacing NETID with your own, and fetch the notebook from our release repository by running the following two git commands:

git fetch release
git merge release/lab_11 -m "Merging initial files"

ONLY IF you get an error related to unrelated histories, use:

git merge release/lab_11 --allow-unrelated-histories -m "Merging initial files"

Part b: Opening the Jupyter Notebooks

One way to open the notebook (may not work)

Open the notebook with the command:

jupyter notebook

Another way to open the notebook: IF you get an error about "jupyter is not recognized" when trying to do this, you can also open the notebook by doing the following.

  • Searching for the "miniconda" program you just downloaded, and run what should say "Anaconda Prompt."
  • This will open up the Anaconda Command Line window that is specifically for running python commands (for instance commands that install python packages or launch jupyter notebooks).
  • If your Anaconda Command line window is not already there, navigate to your stat207 repository (cd Desktop -> cd stat207
  • Run the code in this Anaconda Command Line Prompt window instead
    jupyter notebook

Also another way to open the notebook:

  • Search for the the program "jupyter" on your computer and run it.
  • This will open a window that displays the file system of your computer. Navigate to the folder your notebook is saved in by clicking on the folder links.
  • Once you've found your notebook, click on it to open it

Part c: Editing the Jupyter Notebooks (aka Working on the Assignments)

Inside of the notebook webpage:

  • Navigate into the folder containing the files lab_11_individual.ipynb and lab_11_group.ipynb open up the notebooks
  • Follow the instructions inside of the notebooks.
  • lab_11_individual.ipynb is to be completed individually
  • lab_11_group.ipynb is to be completed in groups of 2-3. Only one person in a group needs to submit this completed group file. Make sure all teammate names are listed in this file.

Whenever you are done, you should checkpoint (using File -> Save Checkpoint in the notebook) your notebook to save your work. Once your work is saved, you can exit the command line running the notebook with Ctrl + C.

Part d: Saving/Submitting your Notebooks back to the Class Repository

When you’re ready to save your work online and/or submit your work, return to the command line and run:

git add -A
git commit -m "submission (or any message here)"
git push origin master

Submitting Your Work

When you have completed working, you should always submit your work (even if you're not quite finished). We will always grade the latest push you made before the due date (and ignore everything else) — submitting multiple times is okay and encouraged!

Inside of Jupyter:

  • Click File -> Save Checkpoint to ensure your notebook is saved.
  • Click File -> Close and Halt to exit your notebook.
  • Click Quit (in the top-right) to close the directory view.

After exiting Jupyter, your command prompt will return to accept new commands. Using your command prompt, run: 

git add -A
git commit -m "submission (or any message here)"
git push origin master

Part e: Verifying your Submission on Github

You can verify your submission was made by visiting the web interface to github: