We are given the following training examples: (1.2, 3.2), (2.8, 8.5), (2,4.7), (0.9, 2.9), (5.1, 11) We want to apply a 3-nearest neighbor rule in order to perform regression. a): Predict the label (real value) at each of the following two points: a1 = 1.5 and X2 = 4.5. Instead of weighing the contribution of each of the 3 nearest neighbors equally, this time we want to perform distance-weighted nearest neighbor regression. What values do we predict now for x1 = 1.5 and x2 = 4.5?

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
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We are given the following training examples:
(1.2, 3.2), (2.8, 8.5), (2,4.7), (0.9, 2.9), (5.1, 11)
We want to apply a 3-nearest neighbor rule in order to perform regression.
(a) :
Predict the label (real value) at each of the following two points: 1 =
1.5 and
x2 = 4.5.
time we want to perform distance-weighted nearest neighbor regression. What values do we
predict now for x1 = 1.5 and x2 = 4.5?
(b).
Instead of weighing the contribution of each of the 3 nearest neighbors equally, this
Transcribed Image Text:We are given the following training examples: (1.2, 3.2), (2.8, 8.5), (2,4.7), (0.9, 2.9), (5.1, 11) We want to apply a 3-nearest neighbor rule in order to perform regression. (a) : Predict the label (real value) at each of the following two points: 1 = 1.5 and x2 = 4.5. time we want to perform distance-weighted nearest neighbor regression. What values do we predict now for x1 = 1.5 and x2 = 4.5? (b). Instead of weighing the contribution of each of the 3 nearest neighbors equally, this
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