A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning
نویسندگان
چکیده
Canonical Correlation Analysis(CCA) is a useful tool to discover relationship between different sources of information represented by vectors. The solution of the underlying optimisation problem involves a generalised eigenproblem and is nonconvex. We will show a sequence of transformations which turn CCA into a convex maximum margin problem. The new formulation can be applied for the same class of problems at a significantly lower computational cost and with a better numerical stability.
منابع مشابه
Generalization of Canonical Correlation Analysis from Multivariate to Functional Cases and its related problems
In multivariate cases, the aim of canonical correlation analysis (CCA) for two sets of variables x and y is to obtain linear combinations of them so that they have the largest possible correlation. However, when x and y are continouse functions of another variable (generally time) in nature, these two functions belong to function spaces which are of infinite dimension, and CCA for them should b...
متن کاملMultivariate Characterisation of Oulmes-Zaer and Tidili Cattle Using the Morphological Traits
Fourteen different morphological traits in 169 and 131 cattle of Oulmes-Zaer and Tidili, respectively were recorded and analyzed using a multivariate approach. The characters measured included heart girth, wither height, rump height, rump length, rump width, chest depth, body length, neck length, cannon circumference, ear length, ear width, head length, horn length and tail length. Breed signif...
متن کاملبررسی رابطه راهبردهای فراشناختی خواندن با اضطراب امتحان در دانشجویان بهداشت حرفهای
Introduction: The previllage of metacognitive knowledge enables the learner's to involve in every moment of their learning activities and the points for which their work progresses and identifies strengths and weaknesses. At the present, the majaroty of academic failures occure on learners because they attempt to learn through inefficient methods. This ...
متن کاملLarge Margin Metric Learning for Multi-Label Prediction
Canonical correlation analysis (CCA) and maximum margin output coding (MMOC) methods have shown promising results for multi-label prediction, where each instance is associated with multiple labels. However, these methods require an expensive decoding procedure to recover the multiple labels of each testing instance. The testing complexity becomes unacceptable when there are many labels. To avoi...
متن کاملCorrelation Pattern between Temperatur, Humidity and Precipitaion by using Functional Canonical Correlation
Understanding dependence structure and relationship between two sets of variables is of main interest in statistics. When encountering two large sets of variables, a researcher can express the relationship between the two sets by extracting only finite linear combinations of the original variables that produce the largest correlations with the second set of variables. When data are con...
متن کامل