Nowadays data mining techniques become more and more popular, however building data driven models we face several independent problems:
These goals are usually mutually exclusive, because building comprehensive model usually assume reduced accuracy, also mining big datasets assumes simplified model. But all these challenges have one thing in common - can be solved by appropriate information selection techniques. The information selection includes - instance and attributes filtering such that
Prototype-based rules or shortly P-Rules is a concept to represent knowledge as a set of rules, however instead of classical propositional logic we propose a logic which is based on reference examples also called prototypes.
In this approach single rule is defined as a reference point (prototype) and some distance measure with or without a threshold.
In general P-Rules can be divided into two separate concepts: