Chaos to Clarity
When data is limited, traditional models struggle. But probabilistic methods can incorporate prior knowledge and update beliefs as new data comes in.
Why do we use probabilistic methods?
• When data is limited, traditional models struggle, but probabilistic methods can incorporate prior knowledge and update decisions as new data comes in.
• Probabilistic models can handle hidden variables, missing data, or uncertain relationships between variables.
• Instead of giving a single prediction, probabilistic models give a distribution of outcomes.
• You can build models that combine domain expertise and uncertainty — and update them over time.
This is powerful in tools like PLANS, where the model adapts as it learns.