The Importance of Disentangling Relationships in Classical E Systems

Independent modeling is an unrealistic assumption for machine learning, as relationships between variables are important in predicting future outcomes and explaining past events./nClassical rule-based systems use rules to represent relationships between variables, which allows for predictions based on a few known variables./nIn addition to disentangling variables, it's essential to disentangle the mechanisms that relate those variables to each other for effective machine learning./nCurrent neural networks are sensitive to catastrophic forgetting, where new learning can destroy previously learned information.