Ontologies are an increasingly important tool in knowledge representation, as they allow large amounts of data to be related in a logical fashion. Current research is concentrated...
Matthew E. Taylor, Cynthia Matuszek, Bryan Klimt, ...
When using machine learning for in silico modeling, the goal is normally to obtain highly accurate predictive models. Often, however, models should also bring insights into intere...
This paper introduces a new algorithm, namely the EquiCorrelation Network (ECON), to perform supervised classification, and regression. ECON is a kernelized LARS-like algorithm, b...
Manuel Loth, Philippe Preux, Samuel Delepoulle, Ch...
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speciï...
Biclustering refers to simultaneously capturing correlations present among subsets of attributes (columns) and records (rows). It is widely used in data mining applications includ...