A group testing method for finding patterns in data
The screening of data sets is essential to modern technology. The use of classical group testing to isolate objects that are individually positive has become the standard experimental procedure in many applied settings. Work is just beginning in applying group testing techniques to the identification of subsets of objects that are collectively positive. This paper addresses the development of probabilistic group testing methods that lead to the identification of positive combinations of objects with specific applications to data mining.
group testing data mining complexes monotone properties maximal frequent sets