1 1 vote A. To drop the least useful variables of a model B. To reduce over-fitting C. To reduce the bias of a model D. To decrease p-value Data Science Interview Questions statistics data-science programming combination + – 0% Accept Rate Accepted 0 answers out of 2 questions Gabriel777 280 points 2 2 5 answer comment Share 0 reply Please log in or register to add a comment.
1 1 vote Answer: B and C - To reduce over-fitting and to reduce the bias of a model. In mathematics, statistics, and computer science, particularly in the fields of machine learning and inverse problems,regularization is a process of introducing additional information in order to solve an ill-posed problem or to prevent overfitting. Source: Wikipedia Gabriel777 answered Oct 27, 2018 Gabriel777 280 points 2 2 5 comment Share See 1 comment 1 1 comment reply tofighi 116k points 73 79 101 commented Oct 27, 2018 reply flag Please provide the links to the sources as well. 0 0 replyShare Please log in or register to add a comment.
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