Question $1($Mandatory$)(2$ points$)$ Which is not a technique for reducing$/$avoiding overfitting in tree induction?Question $1$ options:A$)$ stop growing tree based on the number of training examples at a leafB$)$ reduce tree size by cutting off branches and replacing them with leavesC$)$ choose largest improvement in information gainD$)$ select tree size based on validation dataQuestion $2($Mandatory$)(2$ points$)$ More complex modelsQuestion $2$ options:A$)$ are very interpretableB$)$ are easier to train than simpler modelsC$)$ tend to overfit moreD$)$ have better predictive performanceQuestion $3($Mandatory$)(3$ points$)$ In your job as a data scientist, your boss asks you to help her$/$him evaluate few models that the team as created. All the models were created using the same dataset.In bullet points, explain what you would suggest to your boss on choosing the optimal model.Question $4($Mandatory$)(3$ points$)$ What are the important factors that enabled Amazon to leverage its data and data science capabilities to obtain a significant competitive advantage over traditional "brick and mortar" book stores $($such as Borders$)?$ Please use bullet points.