How does EDA facilitate the identification of important variables in a dataset?
- By exploring relationships between variables and their relation to the outcome variable
- By fitting a predictive model to the data
- By performing a cost-benefit analysis of each variable
- By running a feature importance algorithm on the dataset
EDA facilitates the identification of important variables by exploring relationships between variables and their relation to the outcome variable. Visualizations and summary statistics can highlight which variables have strong relationships with the outcome variable, and these variables are often important for predictive modeling.
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