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Answer :
Discretization can be used to convert the "AnnualIncome" attribute into a binary attribute by setting the threshold at 91000.
Discretization is a data preprocessing technique that transforms continuous variables into discrete categories. In this case, we want to convert the "AnnualIncome" attribute into a binary attribute, indicating whether the income is above or below a certain threshold. By setting the threshold at 91000, we can classify incomes as either high or low.
To perform this discretization, we compare each income value with the threshold. If the income is greater than or equal to 91000, it is assigned a value of 1, representing high income. Conversely, if the income is below 91000, it is assigned a value of 0, indicating low income.
By discretizing the "AnnualIncome" attribute in this manner, we simplify the data representation and enable binary classification based on income levels. This can be useful in various applications, such as segmentation or prediction tasks where income is a relevant factor.
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