A Combined Approach of Data Mining Algorithms Based on Association Rule Mining and Rule Induction
Association rule learning is a popular method for discovering interesting relations between variables in large database. It is often used in market basket analysis domain e.g. if a customer buys onions and potatoes then he buys also beef. But, in fact, it can be implemented in various application areas where the authors want to discover the association between variables. The a priori approach is certainly the most popular. But, despite its good properties, this method has a drawback: the number of obtained rules can be very high. The ability to underline the most interesting rules, those which are relevant, becomes a major challenge.