Canonical Correlation Analysis

Canonical correlation analysis (CCA) is a classical method in statistics and machine learning for handling multi-view data. It seeks linear projections for data from multiple views such that the projected representations share maximal correlation in a common space. It is widely applied in multimodal representation learning and cross-lingual alignment.