Assignment 3 Finished

[Jectrianama]

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

I implemented K-Means clustering (k=3) on the Wine dataset, assigned the cluster labels to each observation, and added them as a new column to the DataFrame. I also performed bootstrapping on the mean of color intensity to compute a 90% confidence interval.

What did you learn from the changes you have made?

I learned how K-Means can group similar samples based on features and how bootstrapping can quantify the uncertainty without strong distributional assumptions.

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

It is possible to try another approaches for clustering.

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

How were these changes tested?

By running each cell of the notebook.

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

N/A

Checklist

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

[Jectrianama]

Mi mistake, sorry