UofT-DSI | LCR - Assignment 1

[brianna-lowe]

UofT-DSI | LCR - Assignment 1

What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)

In completing assignment 1, I added exploratory data analysis, implemented proper train/test splitting with stratification, tuned a KNN model using cross-validation, and evaluated its performance on the test set.

What did you learn from the changes you have made?

I learned how to structure a correct machine learning workflow, including separating predictors and response variables and using cross-validation to tune model hyperparameters.

Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?

I considered standardizing the predictor variables but did not implement this step in the current assignment. This is something I plan to explore in the future to improve model performance and align with best practices for distance-based models.

Were there any challenges? If so, what issue(s) did you face? How did you overcome it?

Evaluating the model required additional understanding beyond the examples shown in Class 2. I overcame this by reviewing relevant documentation, did some trial and error then I applied the current evaluation techniques to the assignment.

**I unintentionally committed class work files while switching to Assignment 1. Please disregard these files, as they were included by mistake.

How were these changes tested?

The changes were tested by verifying class balance after stratified splitting, evaluating model accuracy on the test set, and inspecting predictions using a confusion matrix.

A reference to a related issue in your repository (if applicable)

N/A

Checklist

• I can confirm that my changes are working as intended

[PatelVishakh]

Assignment 1: Pending resubmission.

All Q&A are precisely and concisely answered. Very Nice!

Need to use the Scaled predictors (defined here as predictors_standardized) in Q3) and onwards.

[PatelVishakh]

Assignment 1 Pending submission. Almost there!

I should have said that scaled predictors should be used Q2) and onwards. Sorry about that. but you have repeated the process in Q3) so it is fine.

Question 4) you are using the original data again, but need to use X_train_scaled here.