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Assume that you are working on a data set, explain how would you select important variables?
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Answer / Nirupma Mishra
To select important variables in a dataset, one can use feature selection techniques. Some common methods include: 1) Filter Methods: These methods rank features based on statistical measures (e.g., correlation, variance). 2) Wrapper Methods: These methods evaluate the performance of models with different subsets of features. 3) Embedded Methods: These methods are feature selection techniques that are built into machine learning algorithms (e.g., LASSO regression, random forest).
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