Here is a short dataset consisting of a binary outcome variable Y and two independent variables X1 and X2. The independent variables are normalized, so no need to normalize further.

X1	X2	Y
3	5	1
1	4	0
3	2	0
2	2	1
4	1	1

1. Suppose you are asked to predict the outcome for (X1, X2) = (4, 4). Use KNN with k = 3 to predict this outcome. You can use Euclidean distance as the distance measure.

Predict the outcome with k = 5.

Use k = 3 with Manhattan distance and reevaluate the prediction. Should the prediction with k = 5 change? Why or why not? Is there another name you can use to call the prediction with k = 5.

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