The canonical correlation analysis has been successfully used in many areas aiming to extract important information from a pair of data sets. Thus, the objective this work was determine sample size (number plants) required estimate correlations corn characteristics. Six characteristics were measured 361, 373, and 416 plants, respectively, single, three-way double cross hybrids 2008/2009 crop ye...

Generalized Canonical Correlation Analysis (GCCA) is an important tool that finds numerous applications in data mining, machine learning, and artificial intelligence. It aims at finding `common' random variables are strongly correlated across multiple feature representations (views) of the same set entities. CCA to a lesser extent GCCA have been studied from statistical algorithmic points view,...