TY - JFULL AU - Serkawt Khola PY - 2011/2/ TI - Feature Weighting and Selection - A Novel Genetic Evolutionary Approach T2 - International Journal of Computer and Information Engineering SP - 79 EP - 85 VL - 5 SN - 1307-6892 UR - https://publications.waset.org/pdf/14353 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 49, 2011 N2 - A feature weighting and selection method is proposed which uses the structure of a weightless neuron and exploits the principles that govern the operation of Genetic Algorithms and Evolution. Features are coded onto chromosomes in a novel way which allows weighting information regarding the features to be directly inferred from the gene values. The proposed method is significant in that it addresses several problems concerned with algorithms for feature selection and weighting as well as providing significant advantages such as speed, simplicity and suitability for real-time systems. ER -