The class imbalance problem (when one of the classes has much less samples than the others) is of great importance in machine learning, because it corresponds to many critical app...
In this work, a new learning paradigm called target selection is proposed, which can be used to test for associations between a single genetic variable and a multidimensional, qua...
Johannes Mohr, Sambu Seo, Imke Puis, Andreas Heinz...
We report on three distinct experiments that provide new valuable insights into learning algorithms and datasets. We first describe two effective meta-features that significantly ...
In a distributed system, process synchronization is an important agenda. One of the major duties for process synchronization is mutual exclusion. This paper presents a new central...
Moharram Challenger, Vahid Khalilpour, Peyman Baya...
- Knowledge extraction methods have not efficiently evolved towards new methods to automate the process of building multilingual ontologies as the main representation of structured...