Experiences in building a tool for navigating association rule result sets
Peter Fule, John F. Roddick · 2004
Practical knowledge discovery is an iterative process. First, the experiences gained from one mining run are used to inform the parameter setting and the dataset and attribute selection for subsequent runs. Second, additional data, either incremental additions to existing datasets or the inclusion of additional attributes means that the mining process is reinvoked, perhaps numerous times. Reducing the number of iterations, improving the accuracy of parameter setting and making the results of the mining run more clearly understandable can thus significantly speed up the discovery process.