Question 3:Search and define cosine similarity. Give examples of applications of this similarity measure.Give the pseudo-code of the KNN algorithm.What is the impact of the number of neighbors k on the performance of the KNN algorithm.Given the following data set where X1, X2 and X3 are the descriptive features and Y the target feature. What prediction, the KNN model will return for K=1 and 3? We consider using the Euclidean distance to find similar neighbors for the queries q1 and q2?X1X2X3Y102020741012102019607312165151 QueryX1X2X3 YQ16411K = 1 K = 3 Q28182K = 1 K = 3 Question 3:1. Search and define cosine similarity. Give examples of applications of this similarity measure.2. Give the pseudo-code of the KNN algorithm.3. What is the impact of the number of neighbors k on the performance of the KNN algorithm.4. Given the following data set where X1, X2 and X3 are the descriptive features and Y the targetfeature. What prediction, the KNN model will return for K=1 and 3? We consider using theEuclidean distance to find similar neighbors for the queries q1 and q2?X1X2X3Y10202741012102167312165151Queryq1X1X2X3Y6411K=1K=3q28182K=1K=3

Search and define cosine similarity. Give examples of applications of this similarity measure. Give…

Answered: Search and define cosine similarity.…

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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Question 3:

Search and define cosine similarity. Give examples of applications of this similarity measure.
Give the pseudo-code of the KNN algorithm.
What is the impact of the number of neighbors k on the performance of the KNN algorithm.
Given the following data set where X1, X2 and X3 are the descriptive features and Y the target feature. What prediction, the KNN model will return for K=1 and 3? We consider using the Euclidean distance to find similar neighbors for the queries q1 and q2?

X1	X2	X3	Y
10	20	2	0
7	4	10	1
2	10	2	0
1	9	6	0
7	3	12	1
6	5	15	1

Query	X1	X2	X3		Y
Q1	6	4	11	K = 1
K = 3
Q2	8	18	2	K = 1
K = 3

Question 3:
1. Search and define cosine similarity. Give examples of applications of this similarity measure.
2. Give the pseudo-code of the KNN algorithm.
3. What is the impact of the number of neighbors k on the performance of the KNN algorithm.
4. Given the following data set where X1, X2 and X3 are the descriptive features and Y the target
feature. What prediction, the KNN model will return for K=1 and 3? We consider using the
Euclidean distance to find similar neighbors for the queries q1 and q2?
X1
X2
X3
Y
10
20
2
7
4
10
1
2
10
2
1
6
7
3
12
1
6
5
15
1
Query
q1
X1
X2
X3
Y
6
4
11
K=1
K=3
q2
8
18
2
K=1
K=3

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