Assignment 1

[PSulf]

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

Added my full work for Assignment 1 — step-by-step KNN classification. Includes data inspection, standardization, setting a random seed, splitting the data, using GridSearchCV, and checking accuracy on test data.

What did you learn from the changes you have made?

I got a better understanding of how KNN works and why standardizing features is important. Also learned how to use GridSearchCV properly to tune hyperparameters.

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

I mostly followed the standard path we practiced in the live code, but thought about checking fewer neighbor values just to save time. Ended up doing the full 1–50 range as asked.

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

Nothing major — just had to double-check a few steps to make sure I followed the format from class. Also confirmed that I was on the right Git branch before making edits.

How were these changes tested?

Ran everything in Jupyter Notebook — results looked good. Final test accuracy came out to around 0.955, which makes sense.

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

N/A

Checklist

• I can confirm that my changes are working as intended

[fyellow]

Great job! You met all the criteria