Most known frequent item set mining algorithms work by enumerating candidate item sets and pruning infrequent candidates. An alternative method, which works by intersecting transa...
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Life science researchers frequently need to query large protein data sets in a variety of different ways. Protein data sets have a rich structure that includes its primary structu...
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...