Many data mining algorithms make use of the well-known Inclusion-Exclusion principle. As a consequence, using this principle efficiently is crucial for the success of all these algorithms. Especially in the context of condensed representations, such as NDI, and in computing interesting measures, a quick inclusion-exclusion algorithm can be crucial for the performance. In this paper, we give an overview of several algorithms that depend on the inclusion-exclusion principle and propose an efficient algorithm to use it and evaluate its complexity. The theoretically obtained results are supported by experimental evaluation of the quick IE technique in isolation, and of an example application.
|Title of host publication||Knowledge discovery in inductive databases : 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005 : revised selected papers|
|Editors||F. Bonchi, J.F. Boulicaut|
|Place of Publication||Berlin|
|Publication status||Published - 2005|
|Name||Lecture Notes in Computer Science|