Incremental classification rules based on association rules using formal concept analysis

Concept lattice, core structure in Formal Concept Analysis has been used in various fields like software engineering and knowledge discovery. In this paper, we present the integration of Association rules and Classification rules using Concept Lattice. This gives more accurate classifiers for Classification. The algorithm used is incremental in nature. Any increase in the number of classes, attributes or transactions does not require the access to the previous database. The incremental behavior is very useful in finding classification rules for real time data such as image processing. The algorithm requires just one database pass through the entire database. Individual classes can have different support threshold and pruning conditions such as criteria for noise and number of conditions in the classifier.