Dynamic granularity selection based on local weighted accuracy and local likelihood ratio
Dynamic granularity selection based on local weighted accuracy and local likelihood ratio is a scholarly work, published in 2020 in ''Applied Soft Computing''. The main subjects of the publication include mathematics, artificial intelligence, data mining, statistics, selection (genetic algorithm), Granularity, computer science, and rough set. Granular computing aims to develop a granular view for interpreting and solving problems, in which granularity selection is a key problem and has received extensive attention in recent years.