KNN Regression

Problem

Predict a value for x_test as the mean of the target values of its k nearest neighbors in X_train, using Euclidean distance.

If k exceeds the number of training points, use all of them. Empty training data returns 0.0.

Hint

Sort by squared distance, take the first k targets, and average them.

case 1

in: [[[0,0],[0,1],[10,10],[10,11]],[0,1,10,11],[1,0],2]

expected: 0.5

case 2

in: [[[1],[2],[3],[10]],[2,4,6,20],[4],3]

expected: 4

case 3

in: [[[0,0],[1,1],[2,2]],[0,2,4],[0,0],5]

expected: 2

case 4

in: [[[5,5],[6,5]],[10,16],[4,4],1]

expected: 10

Starter codePython

def knn_regression(X_train, y_train, x_test, k):
    # Your code here
    pass

4 test cases · run your code against them in the editor