Unsupervised feature selection with adaptive residual preserving

Many feature selection approaches are proposed in recent years. Most approaches utilize graph-based methods in studying the structure and relationship among data. However, many data relationships may loss during the graph construction, such as the residual relationships. To better preserve the relationships between data, in this paper, we propose a novel unified learning framework - unsupervised feature selection with adaptive residual...