Use k-nearest neighbor (k=3) with Manhattan distance to classify the node (2,3) with an unknown label as being class A or class B. The training data consists of the following nodes: Node1=(1,1), class A Node2=(0,0), class A Node3=(-1,2), class A Node4=(2,3), class B Node5=(0,-1), class B Node6=(7,10), class B In addition to the final classification, provide the answer for the Manhattan distance calculation between node (2,3) and node3 in the training data.

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
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Use k-nearest neighbor (k=3) with Manhattan distance to classify the node (2,3) with an unknown label as being class A or class B.

The training data consists of the following nodes:
Node1=(1,1), class A
Node2=(0,0), class A
Node3=(-1,2), class A
Node4=(2,3), class B
Node5=(0,-1), class B
Node6=(7,10), class B

In addition to the final classification, provide the answer for the Manhattan distance calculation between node (2,3) and node3 in the training data.

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