P-Models

P-Models are mathematical frameworks used in fields like information theory and machine learning to represent systems where predictions depend on prior data. They focus on how the probability of future events relates to past observations, helping us understand and model complex processes such as language, weather, or biological sequences. Essentially, P-Models provide a structured way to analyze how past information influences what is likely to happen next, enabling efficient predictions and insights in various scientific and technological applications.