Discovery of M-of-N Concepts for Classification

The purpose of knowledge discovery system is to discover interesting patterns in a given database. There exist many types of patterns and this paper focuses on discovery of classification rules from a set of training instances represented by attribute values and class labels. A classification rule restricts values of attributes in its body and predicts a class of an instance that satisfies the body. In usual, a body is a conjunction of conditions on attribute values. This paper deals with a different type of rule whose body is a threshold function and requires at least m of n conditions in it are satisfied. Such kind of rules have much more representation power than rules with conjunctive bodies and are suitable for many real world problems such as diagnoses of diseases in which observation of more symptoms of a certain disease leads more confident diagnosis[3],[8].