Data Mining and Knowledge Discovery Handbook, 2 Edition part 115. 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. | 1120 Nada Lavrac and Blaz Zupan on H and G the result in general is a hierarchy of concepts. For each concept in the hierarchy there is a corresponding function such as H B that determines the dependency of that concept on its immediate descendants in the hierarchy. In terms of data analysis the benefits of function decompositions are Discovery of new data sets that use fewer attributes than the original one and include fewer instances as well. Because of lower complexity such data sets may then be easier to analyze. Each data set represents some concept. Function decomposition organizes discovered concepts in a hierarchy which may itself be interpretable and can help to gain insight into the data relationships and underlying attribute groups. Consider for example a concept hierarchy in Figure that was discovered for a data set that describes a nerve fiber conduction-block Zupan et al. 1997 . The original data set used 2543 instances of six attributes aff nl k-conc na-conc scm leak and a single class variable block determining nerve fiber conducts or not. Function decomposition found three intermediate concepts cl c2 and c3. When interpreted by the domain expert it was found that the discovered intermediate concepts are physiologically meaningful and constitute useful intermediate biophysical properties. Intermediate concept c1 for example couples the concentration of ion channels na-conc and k-conc and ion leakage leak that are all the axonal properties and together influence the combined current source sink capacity of the axon which is the driving force for all propagated action potentials. Moreover new concepts use fewer attributes and instances c1 c2 c3 and the output concept block described 125 25 184 and 65 instances respectively. Intermediate concepts discovered by decomposition can also be regarded as new features that can for example be added to the original example set which can then be examined by 58 Data Mining in Medicine 1121 some other data .
