An introduction to statistical learning: with applications in R
13th Edition
ISBN: 9781461471387
Author: James, Gareth, Witten, Daniela, Hastie, Trevor, TIBSHIRANI, Robert
Publisher: MPS (CC)
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Chapter 2, Problem 5E
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Advantages and disadvantages of flexible approach
- Less flexible and inference is more flexible when a model may not be a perfect fit.
- It fits well for linear models...
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An introduction to statistical learning: with applications in R
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- There are many factors when determining the performance of your model. What are some ways to evaluate regression versus classification models?arrow_forwardAre you aware that one kind of regression analysis is called Summing Squares Regression, or SSR for short?arrow_forwardWrite the objectives of regression testing and what are the situations to perform regression testing?arrow_forward
- What is the difference between discrimination and classification? Between characterization and clustering? Between classification and regression? For each of these pairs of tasks, how are they similar?arrow_forwardIn classification and regression trees (CART), it is done by the model itself, based on how dirty it is. Features that are used in CART are thought to be the most important parts of the tool. Some experts said that people should not have to choose features before they build CART. However, some other analysts disagreed and said that, as long as we need to run models, feature selection is still an important step before building a model. Before running CART models, do you think it is important for users to pick out the features they want to use?arrow_forwardDefine sum of squares regression (SSR)?arrow_forward
- What is a stepwise regression?arrow_forward3. Naïve Bayes Models Describe a classification task from your experience and represent it as a Naïve Bayes model. Make sure to explicitly specify both the labels and the features. You do not need to specify the values of the parameters (those would come from data!). To what extent are the independence assumptions made by a Naïve Bayes model reasonable in your task?arrow_forwardThe validation-set approach allows one to evaluate the performance of different models during model selection. (i) After applying a validation-set approach, the validation errors of two models f1 and f2 are found to be respectively E1 = 10 and E2 = 12. How would you use this result to inform your selectionarrow_forward
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