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ou have a data set which contains Ethno, HbA1c and SBP, indicators in blood. Ethno is a categorical variable and HbA1c and SBP are continuous. They are not evenly distributed. Explain which one of the supervised learning algorithms and why they would be most appropriate for predicting the response Ethno using HbA1c and SBP as the feature variables. The learning algorithms are: Linear Discriminant Analysis, Quadratic Discriminant Analysis and the Naïve Bayes Classifier

ou have a data set which contains Ethno, HbA1c and SBP, indicators in blood. Ethno is a categorical variable and HbA1c and SBP are continuous. They are not evenly distributed. Explain which one of the supervised learning algorithms and why they would be most appropriate for predicting the response Ethno using HbA1c and SBP as the feature variables. The learning algorithms are: Linear Discriminant Analysis, Quadratic Discriminant Analysis and the Naïve Bayes Classifier

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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You have a data set which contains Ethno, HbA1c and SBP, indicators in blood. Ethno is a categorical variable and HbA1c and SBP are continuous. They are not evenly distributed. Explain which one of the supervised learning algorithms and why they would be most appropriate for predicting the response Ethno using HbA1c and SBP as the feature variables. The learning algorithms are: Linear Discriminant Analysis, Quadratic Discriminant Analysis and the Naïve Bayes Classifier

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