LCR - Assignment 1

[ganzichuan]

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

filling in the required code and written responses in the notebook, inspecting the Wine dataset, explaining why predictor variables should be standardized, splitting the data into training and testing sets, tuning the KNN model with cross-validation to find the best number of neighbors, and evaluating the model’s accuracy on the test set

What did you learn from the changes you have made?

how to work with a classification dataset in Python using pandas and scikit-learn; why standardizing predictor variables is important for KNN; practiced with train-test splitting, reproducibility using a fixed random seed, hyperparameter tuning with GridSearchCV, and model evaluation using accuracy

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?

I had a few difficulties figuring out the Python environment on my laptop. I checked the VS Code website and found a solution

How were these changes tested?

They were tested by running the notebook cells and confirming that they executed without errors. I also checked that the outputs matched the expected results.

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

Checklist

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