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Question 4 (K-Nearest Neighbour) Consider that the normalised training set below is part of a K-Nearest Neighbour "model": @relation 'dummy-data-set' @attribute input1 numeric @attribute input2 {a,b,c} @attribute output numeric @data 0.5, a, 10 0, с, 15 1, b, 20 Assume that the input attributes are the first and the second attributes of the training set. What output value would a 3-nearest neighbour (K=3) algorithm predict for an instance with normalised input attributes (0.6, a)? Explain the results.

Question 4 (K-Nearest Neighbour) Consider that the normalised training set below is part of a K-Nearest Neighbour "model": @relation 'dummy-data-set' @attribute input1 numeric @attribute input2 {a,b,c} @attribute output numeric @data 0.5, a, 10 0, с, 15 1, b, 20 Assume that the input attributes are the first and the second attributes of the training set. What output value would a 3-nearest neighbour (K=3) algorithm predict for an instance with normalised input attributes (0.6, a)? Explain the results.

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Question 4 (K-Nearest Neighbour) Consider that the normalised training set below is part of a K-Nearest Neighbour "model": @relation 'dummy-data-set' @attribute inputl numeric @attribute input2 {a,b,c} @attribute output numeric @data 0.5, a, 10 0, с, 15 1, b, 20 Assume that the input attributes are the first and the second attributes of the training set. What output value would a 3-nearest neighbour (K-3) algorithm predict for an instance with normalised input attributes (0.6, a)? Explain the results.
Transcribed Image Text:Question 4 (K-Nearest Neighbour) Consider that the normalised training set below is part of a K-Nearest Neighbour "model": @relation 'dummy-data-set' @attribute inputl numeric @attribute input2 {a,b,c} @attribute output numeric @data 0.5, a, 10 0, с, 15 1, b, 20 Assume that the input attributes are the first and the second attributes of the training set. What output value would a 3-nearest neighbour (K-3) algorithm predict for an instance with normalised input attributes (0.6, a)? Explain the results.
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