عنوان مقاله :
Rough set based feature selection using modified roughmembership function
پديد آورندگان :
sadiq, ahmad t. university of technology - department of computer science, Iraq , maryoush, sura n. al-mustansiriya university - collage of education - computer science department, iraq
چكيده فارسي :
feature selection (FS) is one of the important steps in the knowledge discovery,which aims to reduce the dimensionality of data. In this paper, a feature selectionalgorithm is proposed. The proposed algorithm use the rough membership function,which is modified in order to be suitable for measuring the effectiveness of eachattribute value, and then using it for measuring the effectiveness of each attributethrough a new formula called a modified attribute membership (MAM). Theexperiments shows that the proposed algorithm provides an effective tool for selectingfeature and reducing the dimensionality of data.
كليدواژه :
feature selection , modified rough membership function , modified attributemembership , rough set.
عنوان نشريه :
مجله جامعه كربلاء العلميه
