10 Building and plotting a decision tree
This chapter covers
- Decision-making with and without probabilities
- Maximax and Maximin methods
- Minimax Regret method
- Expected Value method
- Decision trees
Decision-making is a critical process in both personal and professional contexts, where the stakes can be incredibly high—whether it’s managing large sums of money, making career-defining choices, or navigating situations where people’s lives are at risk. In such scenarios, an analytical and systematic approach to decision-making is not just beneficial but essential. Throughout this chapter, we will explore various decision-making methods, with a particular focus on building and plotting decision trees. Unlike the decision trees used in machine learning (see chapter 6), which are designed to classify data, these trees serve as a graphical representation of the decision-making process, outlining possible choices, chance events, associated probabilities, and potential payoffs. This approach helps to systematically determine the best course of action by applying the Expected Value method, which uses probabilities to weigh potential outcomes and make informed decisions.