Abstract The application of data mining algorithms needs a goal-oriented preprocessing of the data. In practical applications the preprocessing task is very time consuming and has ...
Abstract In this paper we propose a novel parallel algorithm for frequent itemset mining. The algorithm is based on the filter-stream programming model, in which the frequent item...
Adriano Veloso, Wagner Meira Jr., Renato Ferreira,...
Evolutionary Algorithms (EAs) are well-known optimization approaches to cope with non-linear, complex problems. These population-based algorithms, however, suffer from a general we...
Shahryar Rahnamayan, Hamid R. Tizhoosh, Magdy M. A...
Background: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractab...
Daniel Wegmann, Christoph Leuenberger, Samuel Neue...
Whenever a dataset has multiple discrete target variables, we want our algorithms to consider not only the variables themselves, but also the interdependencies between them. We pro...
Wouter Duivesteijn, Arno J. Knobbe, Ad Feelders, M...