UofT-DSI | LCR - Assignment 3

[melram17]

Apologies for the late submission as I was away this past weekend

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

Implemented K-Means clustering and bootstrapping for the Wine dataset.

What did you learn from the changes you have made?

Learned how to implement k-means and boot-strapping.

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

No.

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

In my VSCode, kmeans.fit would not work for question 4 (unlike the class demo in which Julia was able to generate an answer). Hence, I had to use external resources and it was recommended to use kmeans.fit_predict

How were these changes tested?

Outputs were used to validate and test changes

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

Question #4 - had to use kmeans.fit_predict which I don't recall seeing in our lectures, not sure why kmeans.fit didn't work on its own

Checklist

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