Apply the Decision Tree algorithm as a basic Machine Learning technique to classify the groups of people according to their FWB $($your dependent variable$).$ Use the formulas provided in our lectures with the Gini Index or Entropy$/$Information Gain and build a model to come to the solution $($You can also search for these on the Internet$).$ You can implement the Tree simply in Excel if you do not use Colab for coding, both options welcomed.

Calculate the Information Gain for each of the SD attributes and rank them according to their importance. Then, if possible, remove the attributes that are not important in predicting FWB and construct the final Decision Tree. Write down the whole process, including formulas, results, explanations in your report below.

As a result, you will have a classification model to predict a person with certain attributes will belong to which group of FWB $($how many groups there are, is described in the Article$).$ If you use Colab, provide the accuracy score and confusion matrix. If you only use Excel, all the formulas and calculations to determine each branch of the Tree should be clearly provided and the Excel model submitted, in order to get the highest score.