The analysis of canonical correlation can bring to light the internal relations between two sets of variables. It has been increasingly used in agricultural experiments and researches.
典型相关分析能揭示出两组变量之间的内在联系，在农业试验研究中应用越来越广泛。
This paper analyzes the change of cultivated land intensive use degree from 1990 to 2006 in China and its influencing factors using canonical correlation analysis.
本文运用典型相关分析方法，对全国1990 - 2006年的耕地利用集约度变化态势及其影响因素进行了分析。
As a new type of algorithm, locality preserving canonical correlation analysis (LPCCA) can solve a large number of non-linear problems.
局部保持的典型相关分析(LPCCA)是一种能够解决大量非线性问题的新型算法。
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