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b) Support Vector Machine (SVM) uses a concept of hyperplane to divide the data into classes. However, there is an infinite number of hyperplanes dividing the classes. Which hyperplane is the best choice? What are the support vectors and what is the impact of removing any support vector from the given data set? d) Differentiate between false positives and false negatives computed by a machine learning model. Which error, a false negative or a false positive, would be considered more damaging from the standpoint of the lending institution who gives loan to the applicants? Justify your answer.

b) Support Vector Machine (SVM) uses a concept of hyperplane to divide the data into classes. However, there is an infinite number of hyperplanes dividing the classes. Which hyperplane is the best choice? What are the support vectors and what is the impact of removing any support vector from the given data set? d) Differentiate between false positives and false negatives computed by a machine learning model. Which error, a false negative or a false positive, would be considered more damaging from the standpoint of the lending institution who gives loan to the applicants? Justify your answer.

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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b) Support Vector Machine (SVM) uses a concept of hyperplane to divide the data into classes. However, there is an infinite number of hyperplanes dividing the classes. Which hyperplane is the best choice? What are the support vectors and what is the impact of removing any support vector from the given data set? d) Differentiate between false positives and false negatives computed by a machine learning model. Which error, a false negative or a false positive, would be considered more damaging from the standpoint of the lending institution who gives loan to the applicants? Justify your answer.
Transcribed Image Text:b) Support Vector Machine (SVM) uses a concept of hyperplane to divide the data into classes. However, there is an infinite number of hyperplanes dividing the classes. Which hyperplane is the best choice? What are the support vectors and what is the impact of removing any support vector from the given data set? d) Differentiate between false positives and false negatives computed by a machine learning model. Which error, a false negative or a false positive, would be considered more damaging from the standpoint of the lending institution who gives loan to the applicants? Justify your answer.
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