Multi-View Fuzzy Logic System with the Cooperation between Visible and
  Hidden Views
  Multi-view datasets are frequently encountered in learning tasks, such as web
data mining and multimedia information analysis. Given a multi-view dataset,
traditional learning algorithms usually decompose it into several single-view
datasets, from each of which a single-view model is learned. In contrast, a
multi-view learning algorithm can achieve better performance by cooperative
learning on the multi-view data. However, existing multi-view approaches mainly
focus on the views that are visible and ignore the hidden information behind
the visible views, which usually contains some intrinsic information of the
multi-view data, or vice versa. To address this problem, this paper proposes a
multi-view fuzzy logic system, which utilizes both the hidden information
shared by the multiple visible views and the information of each visible view.
Extensive experiments were conducted to validate its effectiveness.
