"Sparse fuzzy classification for profiling online users and relevant us" by Jie Yang, Brian Yecies et al.
Extracting information and knowledge from users’ online activity is of great significance for a variety of practical purposes. Yet, existing research suffers from limitations including requiring prior knowledge and poor interpretability. In this study, we develop a novel classification algorithm based on the dual concepts of fuzzy set and sparsity regularization. Specifically, the proposed algorithm introduces two types of fuzzy sets designed to fuzzify samples, then the membership criteria from resultant fuzzy sets is further cast as the soft feature for training a sparse classifier. To dem...