Feature creep, if not managed well, cause software bloat. This in turn makes software applications become slower. Currently, software industry urgently requires mechanisms and approaches to reduce unnecessary or low value features. In this paper, we introduce a modelling notation, so called Feature Usage Diagram, and an approach to identify and visualize the required information for decision ma...

artificial immune systems (ais) can be defined as soft computing systems inspired by immune system of vertebrates. immune system is an adaptive pattern recognition system. ais have been used in pattern recognition, machine learning, optimization and clustering. feature reduction refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encoun...

Feature selection is a classical problem in machine learning, and how to design a method to select the features that can contain all the internal semantic correlation of the original feature set is a challenge. The authors present a general approach to select features via rough set based reduction, which can keep the selected features with the same semantic correlation as the original feature s...

Artificial Immune Systems (AIS) can be defined as soft computing systems inspired by immune system of vertebrates. Immune system is an adaptive pattern recognition system. AIS have been used in pattern recognition, machine learning, optimization and clustering. Feature reduction refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encoun...

brain-computer interface systems are a new mode of communication which provides a new path between brain and its surrounding by processing eeg signals measured in different mental states.  therefore, choosing suitable features is demanded for a good bci communication. in this regard, one of the points to be considered is feature vector dimensionality. we present a method of feature reduction us...