1. Based on the results of above exercise, answer the following questions: What would be the...
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1. Based on the results of above exercise, answer the following questions: What would be the issues in this dataset in terms of data ethics? Will the model performance be impacted if the gender feature (male and female) is removed from the model (but you still have it available separately to do the two confusion matrices)? 2. Identify a distinct real-world case or dataset and respond to the following questions: Briefly discuss the selected case. What are the data ethics issues involved? Hint: Consider including PRINCIPLES OF DATA ETHICS such as privacy, security, fairness, data ownership, transparency, and accountability. Provide your insights into the possible causes of these issues and suggest ways to mitigate them. References: [1] UBC 2022 Summer Applied Machine Learning, Instructor: Mehrdad Oveisi. [2] https://scikit-learn.org/stable/modules/classes.html#module-sklearn.impute [3] https://scikit-learn.org/stable/modules/classes.html#module-sklearn.preprocessing 1. Based on the results of above exercise, answer the following questions: What would be the issues in this dataset in terms of data ethics? Will the model performance be impacted if the gender feature (male and female) is removed from the model (but you still have it available separately to do the two confusion matrices)? 2. Identify a distinct real-world case or dataset and respond to the following questions: Briefly discuss the selected case. What are the data ethics issues involved? Hint: Consider including PRINCIPLES OF DATA ETHICS such as privacy, security, fairness, data ownership, transparency, and accountability. Provide your insights into the possible causes of these issues and suggest ways to mitigate them. References: [1] UBC 2022 Summer Applied Machine Learning, Instructor: Mehrdad Oveisi. [2] https://scikit-learn.org/stable/modules/classes.html#module-sklearn.impute [3] https://scikit-learn.org/stable/modules/classes.html#module-sklearn.preprocessing
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Related Book For
Applied Regression Analysis and Other Multivariable Methods
ISBN: 978-1285051086
5th edition
Authors: David G. Kleinbaum, Lawrence L. Kupper, Azhar Nizam, Eli S. Rosenberg
Posted Date:
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