The paper presents MRNet, an original method for inferring genetic networks from microarray data. This method is based on maximum relevance/minimum redundancy (MRMR), an effective ...
Patrick Emmanuel Meyer, Kevin Kontos, Gianluca Bon...
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...
With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive ...
We present a Genetic Algorithm based feature selection approach according to which feature subsets are represented by individuals of an evolving population. Evolution is controlle...
Luigi P. Cordella, Claudio De Stefano, Francesco F...
Background: Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of ide...