Assignment 1

[bhuiyaau]

UofT-DSI | LCR - Assignment 1

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

I added code and used our live codes to make changes for the wine data set.

What did you learn from the changes you have made?

I did data inspections, processing, data splitting for testing and training data, model initialization and cross-validation

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

No, I followed the live codes and how they were used in the class lectures.

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

Yes, I continue to have challenges with github, I tried googling and reviewing videos, but ultimately needed help from staff

How were these changes tested?

I used the print option

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

Checklist

• [X ] I can confirm that my changes are working as intended

[anjali-deshpande-hub]

Well done.

Some corrections:
Question 2 (i) Why is it important to standardize the predictor variables?
Standardization doesn’t make features “equal to the distance.” as stated.

Without standardization, features with larger scales can dominate the distance and bias the identification of nearest neighbours. Standardization ensures that all features are on a similar scale, so each feature contributes fairly.

Question 2 (iii) Why is setting a seed important?

Setting a seed is important because it ensures that the random processes (like data splitting or random initialization) produce the same results each time the code is run, which makes experiments reproducible.

Question 3 (iv) Also, print the best KNN value by printing wine_tune_grid.best_params_

[anjali-deshpande-hub]

The changes look good. Well done! Thank you.