Memory-Based Learning

Memory-Based Learning refers to a method where knowledge is acquired and stored based on past experiences or examples. Instead of creating detailed models from scratch, this approach relies on specific instances or memories to make decisions or predictions. For example, when faced with a new situation, a person might recall similar past experiences to guide their response. This technique is particularly useful in fields like recommendation systems, where previous behavior helps suggest relevant choices, making it a practical way to leverage existing information for future learning and decision-making.