K-nearest neighbor classification : As shown in the table below, there are seven three-dimensional data points, among which six are labeled and one is unlabeled. Please determine the label of data point by using the K-nearest neighbor classification method according to the Euclidean distance metric. data points A(7,3,9) B(6,2,1) C(7,10,9) D(8,1,6) E(1,6,7) F(9,7,3) G(9,1,7) label 1 1 2 2 1 1 unknown The definition of Euclidean distance is given below. If you are given two data points, i.e., A = (a₁, a2, a3) and B = (b₁,b₂, b), then Euclidean distance between A and B can be calculated by distance(A, B) = √(a₁ − b₁)² + (a2 − b2)² + (a3 − b3)². a) Please calculate the Euclidean distances between point and the other points, and fill in the table below. distance(A, G) distance(B,G)| distance(C, G) | distance(D, G) | distance(E, G) | distance(F, G) b) Please determine the label of the data point ( based on the 1-nearest neighbor method (i.e., k = 1). c) Please determine the label of the data point based on the 3-nearest neighbors method (i.e., k = 3). d) Please implement the above three questions by coding and paste your codes below. For example, you can paste your Matlab or Python codes below (other programming languages are also welcome).
K-nearest neighbor classification : As shown in the table below, there are seven three-dimensional data points, among which six are labeled and one is unlabeled. Please determine the label of data point by using the K-nearest neighbor classification method according to the Euclidean distance metric. data points A(7,3,9) B(6,2,1) C(7,10,9) D(8,1,6) E(1,6,7) F(9,7,3) G(9,1,7) label 1 1 2 2 1 1 unknown The definition of Euclidean distance is given below. If you are given two data points, i.e., A = (a₁, a2, a3) and B = (b₁,b₂, b), then Euclidean distance between A and B can be calculated by distance(A, B) = √(a₁ − b₁)² + (a2 − b2)² + (a3 − b3)². a) Please calculate the Euclidean distances between point and the other points, and fill in the table below. distance(A, G) distance(B,G)| distance(C, G) | distance(D, G) | distance(E, G) | distance(F, G) b) Please determine the label of the data point ( based on the 1-nearest neighbor method (i.e., k = 1). c) Please determine the label of the data point based on the 3-nearest neighbors method (i.e., k = 3). d) Please implement the above three questions by coding and paste your codes below. For example, you can paste your Matlab or Python codes below (other programming languages are also welcome).
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Hello Expert, could you please help me for solving this question (b)(c)(d)
thank you so much
Transcribed Image Text:K-nearest neighbor classification : As shown in the table below, there are seven three-dimensional
data points, among which six are labeled and one is unlabeled. Please determine the label of data point
C by using the K-nearest neighbor classification method according to the Euclidean distance metric.
data points
A(7,3,9)
B(6,2,1)
C(7,10,9)
D(8,1,6)
E(1,6,7)
F(9,7,3)
G(9,1,7)
label
1
1
2
2
1
1
unknown
The definition of Euclidean distance is given below. If you are given two data points, i.e.,
A = (a₁, a2, a3) and B (b₁,b2, 63), then Euclidean distance between A and B can be calculated by
distance (A, B) = √(a1 − b₁)² + (a₂ b₂)² + (a3 -b3)².
=
a) Please calculate the Euclidean distances between point and the other points, and fill in the table
below.
distance(A, G) | distance(B,G) distance(C, G)
distance(D, G) | distance(E, G) | distance(F, G)
b) Please determine the label of the data point based on the 1-nearest neighbor method (i.e., k = 1).
c) Please determine the label of the data point ( based on the 3-nearest neighbors method (i.e.,
k = 3).
d) Please implement the above three questions by coding and paste your codes below. For example,
you can paste your Matlab or Python codes below (other programming languages are also
welcome).
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