Data Mining and Knowledge Discovery Handbook, 2 Edition part 29. Knowledge Discovery demonstrates intelligent computing at its best, and is the most desirable and interesting end-product of Information Technology. To be able to discover and to extract knowledge from data is a task that many researchers and practitioners are endeavoring to accomplish. There is a lot of hidden knowledge waiting to be discovered – this is the challenge created by today’s abundance of data. Data Mining and Knowledge Discovery Handbook, 2nd Edition organizes the most current concepts, theories, standards, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery. | 260 Jerzy W. Grzymala-Busse AQ Another rule induction algorithm developed by R. S. Michalski and his collaborators in the early seventies is an algorithm called AQ. Many versions of the algorithm have been developed under different names Michalski et al. 1986A Michalski et al. 1986A . Let us start by quoting some definitions from Michalski et al. 1986A Michalski et al. 1986A . Let A be the set of all attributes A A1 A2 . Ak . A seed is a member of the concept . a positive case. A selector is an expression that associates a variable attribute or decision to a value of the variable . a negation of value a disjunction of values etc. A complex is a conjunction of selectors. A partial star G e e1 is a set of all complexes describing the seed e x1 x2 . xk and not describing a negative case e1 y1 y2 . yk . Thus the complexes of G e e1 are conjunctions of selectors of the form A -yi for all i such that xi yi. A star G e F is constructed from all partial stars G e ei for all ei e F and by conjuncting these partial stars by each other using absorption law to eliminate redundancy. For a given concept C a cover is a disjunction of complexes describing all positive cases from C and not describing any negative cases from F U - C. The main idea of the AQ algorithm is to generate a cover for each concept by computing stars and selecting from them single complexes to the cover. For the example from Table and concept C 1 2 4 5 described by Flu yes set F of negative cases is equal to 3 6 7. A seed is any member of C say that it is case 1. Then the partial star G 1 3 is equal to Temperature normal Headache no Weakness no . Obviously partial star G 1 3 describes negative cases 6 and 7. The partial star G 1 6 equals Temperature high Headache no Weakness no The conjunct of G 1 3 and G 1 6 is equal to Temperature very .high Temperature normal Headache no Temperature normal Weakness no Temperature high Headache no H ead ache no H ead ache no Weakness no T em perat ure .
