Decision Tree
Encord Computer Vision Glossary
Decision tree
A decision tree is a diagram that shows how decisions are made. In order to make the optimal choice, it is used to weigh the pros and cons of several options. The branches of the decision tree represent many options that could result from each decision point, or node.
The decision-maker is presented with a choice at the root node, where the process starts. The tree then branches out into other potential outcomes, each of which is represented by a child node. The tree might have a branch for "purchase a new automobile" and another branch for "buy a used car," for instance, if the choice is whether to buy a car.
As the tree progresses, the decision-maker must evaluate the pros and cons of each choice and decide which outcome is most desirable. The tree will continue to branch out until the decision-maker reaches a terminal node, or leaf, which represents the final decision.
What is a decision tree in computer vision?
Decision trees can be useful for a wide range of applications, including business, finance, and healthcare. They can be used to evaluate the potential risks and rewards of a particular decision, or to identify the most cost-effective option.
Decision trees have the major benefit of being simple to comprehend and explain to others. Making judgements based on them is simple because they can be easily visualized and discussed.
Overall, decision trees are an effective tool for making decisions because they let decision-makers weigh a variety of possibilities and assess their prospective effects in a structured and logical way.
