One element in cleaning the data set in the mining process involves A) removing unimportant variables B) adding more variables to the data set C) calculating the adjusted R² D) calculating the coefficient of multiple correlation

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Removing unimportant variables is a common step in cleaning a data set during the mining process. This helps to simplify the data set and focus on the relevant variables that can provide insight and value in the analysis. Adding more variables can actually make the data set more complex and potentially add noise to the results. Calculating adjusted R² and coefficient of multiple correlation are not typically involved in cleaning a data set, but may be used in later stages of the mining process for analysis and modeling.

One Element in Cleaning the Data Set in the Mining