How does KEEL compare to curve fitting approaches?
A common practice is to measure the real world and attempt to create a “formula” from the data accumulated. This approach is used when there is little (or no) “understanding” of the problem. By “understanding” we mean that an expert doesn’t know enough about the problem to describe it in a formula. Data is used to derive a synthetic understanding. This approach may use some kind of curve fitting (pattern matching) approach. One risk to this type of approach is that the measured data may be subject to external influences that may not have been measured or accumulated in the dataset. This results in “garbage in – garbage out” types of problems. If this happens, one may not even recognize that there is a problem. It is often difficult to trace back to how the data was gathered and accumulated. With KEEL, one uses a human’s understanding (even if it is limited), to model the system. The dynamic nature of the KEEL language helps the human test the model under various scenarios by stimulatin
