Feedback on Linear Regression Assignment

Be curious!

LLMs!

Carlijn & Georgia

  • Commits
  • Good explanatory text and layout.
  • Good residual and scale location plots. But what can we do about the nonlinearity and heteroscadisticity?
  • Correlations: what steps to take?
  • Think about your layout in the answers to 9c
  • 9d scale location and influence plots are not the prettiest. How could you make the plot more readable?
  • "…exclusion from the model would likely result in a noticeable change in the estimated coefficients."

Emil, Adrian, Louanne

  • No report, just code
  • Where to look? Various files.
  • Comments in Python files
  • Spider file headers

    # -*- coding: utf-8 -*-
            """
            Created on Thu Sep 25 12:19:18 2025
    
            @author: seinc
            """
    
  • You might consider a separate file for imports and setup.

Matúš, Jesse, Nora

  • Single repo. We will use one repo per assignment.
  • Lab1 in Python file. Clear code with comments.
  • Lab2 files not obvious to find.
  • Clearly laid out. Good formatting
  • "High multicollinearity may require careful handling in regression"
  • "significant contributors to predicting mpg"
  • QQ-plots good!
  • Lots of plots!
  • Commits
  • Watch out for how some editors save your files
  • .gitignore and .DS_Store in this commit

Madalina, Natalia

  • Week 1

Yaohong, Natalia

  • Many commits by Natalia
  • Short direct answers in the beginning. Better explanations later.

Roman, Lynn

  • lviss
  • Lots of Roman
  • Commit messages
  • Put yourself into the reader's shoes.
  • Images of text!

Janina and Mariana

  • Most balanced commit history!
  • Images subdir
  • Step by step explanation
  • Good formatting. Drawing attention to results in bold.
  • Don't let plots get too "busy". See Tufte
  • Something went wrong with the formatting.

Max

  • Commented code for exercises.

Nora and Jagoda

Fridolin & Efraim

  • Plots with little explanation
  • Selecting many columns

    desc_stat = auto.select(
        pl.col("mpg"),
        pl.col("cylinders"),
        pl.col("displacement"),
        pl.col("horsepower"),
        pl.col("weight"),
        pl.col("acceleration"),
        pl.col("year"),
    ).describe()
    
    desc_stat = auto.select(
        [
            "mpg",
            "cylinders",
            "displacement",
            "horsepower",
            "weight",
            "acceleration",
            "year",
        ],
    ).describe()
    
  • Same applies to savefig as to reading data. Better use relative dir

    plot_9_d.savefig(
        "/Users/efraimtoth/Library/CloudStorage/OneDrive-UvA/AUC/3rd year/Machine Learning/repos/lab1/Images/auto_pairplot.png"
    )
    

Efraim & Romane

Yaohong & Emil

  • In Python files with comments
  • Each one did a complete lab.

Author: Breanndán Ó Nualláin <o@uva.nl>

Date: 2025-09-29 Mon 13:54