 The importance of prior knowledge in machine learning is suggested by its role in search and optimization.Loosely, the no free lunch theorem states that all search algorithms have the same average performance over all problems, and thus implies that to gain in performance on a certain application one must use a specialized algorithm that includes some prior knowledge about the problem.The different types of prior knowledge encountered in pattern recognition are now regrouped under two main categories