This article provides an outline on a recent application of soft computing for the mining of microarray gene expressions.We describe investigations with an evolutionary-rough feature selection algorithm for feature se...This article provides an outline on a recent application of soft computing for the mining of microarray gene expressions.We describe investigations with an evolutionary-rough feature selection algorithm for feature selection and classification on cancer data.Rough set theory is employed to generate reducts,which represent the minimal sets of non-redundant features capable of discerning between all objects,in a multi-objective framework.The experimental results demonstrate the effectiveness of the methodology on three cancer datasets.展开更多
文摘This article provides an outline on a recent application of soft computing for the mining of microarray gene expressions.We describe investigations with an evolutionary-rough feature selection algorithm for feature selection and classification on cancer data.Rough set theory is employed to generate reducts,which represent the minimal sets of non-redundant features capable of discerning between all objects,in a multi-objective framework.The experimental results demonstrate the effectiveness of the methodology on three cancer datasets.
