How is the concept of “surprise” handled by KEEL Technology (compared to ANN)?
One of the problems with ANN-based (Artificial Neural Net) solutions is that they do not react well to surprise. ANN-based systems are pattern matching systems that are taught. If they have not been taught a particular pattern of inputs, they will just interpolate between what they have been taught and create an answer. With KEEL, one describes how to interpret information, not patterns. There is no interpolation between taught points. The concept of “surprise” can be decomposed at multiple levels. First, one can encounter scenarios with a known set of inputs combined in unexpected ways. With KEEL, one can examine the system and observe how it was interpreted. If changes are needed they can easily be made. With ANN there is no way to know “how” an answer was derived, so it can only be addressed with increased training. Another way of decomposing “surprise” is for a system to encounter new variables that impact the problem domain that were never before considered. This would be like a “
