As data sets become increasingly complex, it becomes more difficult to discern patterns and relationships using traditional methods of interpretation. In these cases, artificial intelligence (AI) can be immensely helpful. AI provides new ways of looking at data that can be more effective at finding patterns. Additionally, neural networks – which are a type of machine learning method – can be used to interpret decision trees. This is because they are able to learn relationships between different inputs and outputs, which can be used to understand the decision tree.
Overall, AI can provide new and creative ways of interpreting decision trees that are difficult to interpret. This can be helpful in many situations, as it can allow for a better understanding of the data and lead to more informed decision-making.
References:
https://aisights.com/use-artificial-intelligence-to-interpret-decision-trees/https://towardsdatascience.com/artificial-intelligence-for-decision-trees-725148dda1b2
https://www.nature.com/articles/s42256-019-0016-z