ISYE 6501 - Midterm 2 Exam questions and answers Graded A+ latest update when might overfitting occur when the # of factors is close to or larger than the # of data points causing the model to potentially fit too closely to random effects Why are sim
ISYE 6501 - Midterm 2 Exam questions and answers Graded A+ latest update when might overfitting occur when the # of factors is close to or larger than the # of data points causing the model to potentially fit too closely to random effects Why are simple models better than complex ones less data is required; less chance of insignificant factors and easier to interpret what is forward selection we select the best new factor and see if it's good enough (R^2, AIC, or p-value) add it to our model and fit the model with the current set of factors. Then at the end we remove factors that are lower than a certain threshold what is backward elimination we start with all factors and find the worst on a supplied threshold (p = 0.15). If it is worse we remove it and start the process over. We do that until we have the number of factors that we want and then we move the factors lower than a second threshold (p = .05) and fit the model with all set of factors what is stepwise regression it is a combination of forward selection and backward elimination. We can either start with all factors or no factors and
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