Problem 1: Handling Missing Values [20] Given the following data set with 10 data points and 4 attributes, and the final column represents the label of the data points. There are missing values in the data, replace those missing values with any one of the methods discussed in class. Comment on why you think the method you used is the most suitable. ID Age Income Spending Label S1 18 12K 12K Low S2 22 ? 13K Low S3 27 70K ? Middle S4 29 120K 70K Middle S5 ? 125K 65K Middle S6 35 250K 80K Upper S7 42 ? 100K Upper S8 ? 350K 150K Upper S9 36 130K ? Middle S10 19 35K 32K Low *using R is optional for this task