Simultaneously Combining Multi-view Multi-label Learning with Maximum Margin Classification

Multiple feature views arise in various important data classification scenarios. However, finding a consensus feature view from multiple feature views for a classifier is still a challenging task. We present a new classification framework using the multi-label correlation information to address the problem of simultaneously combining multiple feature views and maximum margin classification. Under this framework, we propose a novel algorithm that...