Learning from imbalanced datasets presents a convoluted problem both from the modeling and cost standpoints. In particular, when a class is of great interest but occurs relatively...
Nitesh V. Chawla, David A. Cieslak, Lawrence O. Ha...
In the last few decades, several studies have found the same technology implemented in highly similar organizational settings to be associated with very different consequences for...
We present a new method, called UTAGMS , for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. ...
Salvatore Greco, Vincent Mousseau, Roman Slowinski
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
Background: Quantitative descriptions of amino acid similarity, expressed as probabilistic models of evolutionary interchangeability, are central to many mainstream bioinformatic ...
Blazej Bulka, Marie desJardins, Stephen J. Freelan...