NFL

In computer science, „NFL“ stands for the No Free Lunch theorem. This theorem is applicable in the context of optimization and machine learning. It essentially states that no optimization algorithm is universally superior to all others when averaged across all possible problems. In other words, if an algorithm performs well on one specific type of problem, it will perform poorly on average on other types of problems. The implications of the No Free Lunch theorem highlight the importance of selecting algorithms based on the characteristics of the specific problem being solved rather than relying on a single algorithm for all scenarios. This underlines the necessity of understanding the problem domain and the performance trade-offs of various algorithms in practice.