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What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)
Complete the assignment by inspecting the dataset, standardizing predictor variables, splitting data into training/testing sets, tuning n_neighbors with grid search, and evaluating the model's accuracy.
What did you learn from the changes you have made?
Using GridSearchCV to do grid search and find the best parameter for knn.
Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?
Yes, I originally wanted to use train_test_split for data splitting.
Were there any challenges? If so, what issue(s) did you face? How did you overcome it?
How were these changes tested?
By verifying data split proportions, confirming grid search results, and evaluating model accuracy on the test set.
A reference to a related issue in your repository (if applicable)
Checklist