NRough is focused on rough set based algorithms for feature selection and classification i.e. computation of various types of decision reducts, bireducts, decision reduct ensembles and rough set inspired decision rule induction. The framework however contains more routines and algorithms for supervised and unsupervised learning. Its architecture allows easy extendability and integration. NRough is written in CSharp and compliant with .NET Common Language Specification (CLS).

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