ISYE 6501 -Exam 2 Wks 8 – 12 Exam | Questions & 100% Correct Answers (Verified) | Latest Update | Grade A+
Building simpler models with fewer factors helps avoid which problems? A. Overfitting B. Low prediction quality C. Bias in the most important factors D. Difficulty in interpretation : A. Overfitting D. Difficulty of interpretation Two main reasons to limit # of factors in a model. : 1. Overfitting 2. Simplicity When is overfitting likely to happen? : When the number of factors is close to the number of data points. 2 | P a g e How does using a # of factors that is close to the number of data points cause overfitting? : The model too closely fits the random efffects. It fits that data set well, but fails to predict well on a new data set. Three reasons simple models are better than complex models. : 1. Less data is required 2. Less chance of including insignificant factors 3. Easier to interpret
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