CTW

CTW, or Context-Tree Weighting, is a method used in data compression and prediction. It models sequences by considering past patterns (contexts) and combines them to predict future data. Imagine it as a decision tree that adapts as it learns, weighing different historical patterns based on their likelihood. This approach efficiently captures dependencies in data, improving compression and prediction accuracy without needing to store all possible patterns. Overall, CTW is a powerful algorithm that dynamically balances simplicity and complexity to understand and encode data sequences effectively.