Semantics-preserving dimensionality reduction refers to the problem of selecting those input
features that are most predictive of a given outcome; a problem encountered in many areas …

The rough and fuzzy set approaches presented here open up many new frontiers for
continued research and development Computational Intelligence and Feature Selection …

The fuzzy rough set is one of the most effective methods for dealing with the fuzziness and
uncertainty of data. However, in most cases this model only considers the information …

Attribute selection (AS) refers to the problem of selecting those input attributes or features
that are most predictive of a given outcome; a problem encountered in many areas such as …

Feature selection is a process of selecting optimal features that produce the most prognostic
outcome. It is one of the essential steps in knowledge discovery. The crisis is that not all …

Rough set theory provides a methodology for data analysis based on the approximation of
concepts in information systems. It revolves around the notion of discernibility: the ability to …

Plant diseases is one of the major bottlenecks in agricultural production that have bad
effects on the economic of any country. Automatic detection of such disease could minimize …

Feature selection refers to the problem of selecting those input features that are most
predictive of a given outcome; a problem encountered in many areas such as machine …