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Consider the perfume dataset in the file, it contains the strength of the smell of 20 perfumes measured by an odor meter throughout 25 seconds, so each second (column) is a new measurement. Write a program to group these perfumes based on the similarity in the strength of their smell. You should use k-means clustering algorithm. The final output of your program should show k lists of perfumes, and show outlier perfume's records (if exists).

Consider the perfume dataset in the file, it contains the strength of the smell of 20 perfumes measured by an odor meter throughout 25 seconds, so each second (column) is a new measurement. Write a program to group these perfumes based on the similarity in the strength of their smell. You should use k-means clustering algorithm. The final output of your program should show k lists of perfumes, and show outlier perfume's records (if exists).

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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Computer Science Consider the perfume dataset in the file, it contains the strength of the smell of 20 perfumes measured by an odor meter throughout 25 seconds, so each second (column) is a new measurement. Write a program to group these perfumes based on the similarity in the strength of their smell. You should use k-means clustering algorithm. The final output of your program should show lists of perfumes, and show outlier perfume's records (if exists).
Transcribed Image Text:Computer Science Consider the perfume dataset in the file, it contains the strength of the smell of 20 perfumes measured by an odor meter throughout 25 seconds, so each second (column) is a new measurement. Write a program to group these perfumes based on the similarity in the strength of their smell. You should use k-means clustering algorithm. The final output of your program should show lists of perfumes, and show outlier perfume's records (if exists).
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