Clustering was created to speed up k nearest neighbor (KNN) classification. Could clustering result in a more precise classifier? Explain in brief detail why.
Clustering was created to speed up k nearest neighbor (KNN) classification. Could clustering result in a more precise classifier? Explain in brief detail why.
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
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Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Transcribed Image Text:Clustering was created to speed up k nearest neighbor (kNN) classification. Could
clustering result in a more precise classifier? Explain in brief detail why.
Expert Solution
Step 1
The number of neighbors, k, is the single parameter that may modify the level of difficulty of the KNN algorithm. The smoothness of the categorization border increases as k becomes higher. Alternately, we may consider that as k grows, the complexity of KNN decreases.
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