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A Tutorial on Canonical Correlation Methods [PDF]
ACM Computing Surveys, 2017 Canonical correlation analysis is a family of multivariate statistical methods for the analysis of paired sets of variables. Since its proposition, canonical correlation analysis has, for instance, been extended to extract relations between two sets of variables when the sample size is insufficient in relation to the data dimensionality, when the ...
Monteiro, João M +6 more
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Non‐linear canonical correlation† [PDF]
British Journal of Mathematical and Statistical Psychology, 1983 Non‐linear canonical correlation analysis is a method for canonical correlation analysis with optimal scaling features. The method fits many kinds of discrete data. The different parameters are solved for in an alternating least squares way and the corresponding program is called CANALS.
van der Burg, Eeke, de Leeuw, Jan
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Canonical Correlations and Nonlinear Dependencies [PDF]
Symmetry, 2021 Canonical correlation analysis (CCA) is the default method for investigating the linear dependence structure between two random vectors, but it might not detect nonlinear dependencies. This paper models the nonlinear dependencies between two random vectors by the perturbed independence distribution, a multivariate semiparametric model where CCA ...
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Incremental Canonical Correlation Analysis
Applied Sciences, 2020 Canonical correlation analysis (CCA) is a kind of a simple yet effective multiview feature learning technique. In general, it learns separate subspaces for two views by maximizing their correlations.
Hongmin Zhao, Dongting Sun, Zhigang Luo
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Sparse canonical correlation analysis [PDF]
Machine Learning, 2010 We present a novel method for solving Canonical Correlation Analysis (CCA) in a sparse convex framework using a least squares approach. The presented method focuses on the scenario when one is interested in (or limited to) a primal representation for the first view while having a dual representation for the second view.
David R. Hardoon, John Shawe-Taylor
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Canonical Correlation Analysis to Biomass CHONS Prediction
Chemical Engineering Transactions, 2023 Fermentation biomasses can be defined as a complex mixture of different natural components and microbes, having biodegradable and organic waste as the primary source. Its correct characterization is crucial to have proper processing in fermentative units.
Federico Moretta +4 more
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Supervised Canonical Correlation Analysis Based on Deep Learning [PDF]
Jisuanji gongcheng, 2022 Canonical Correlation Analysis (CCA) is a multivariate statistical method, which uses the correlation between comprehensive variable pairs to reflect the overall correlation between two groups of indicators.The traditional CCA method can not effectively ...
ZHANG Heng, CHEN Xiaohong, LAN Yuxiang, LI Shunming
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Canonical Correlation between Fathering and Emotional Autonomy [PDF]
Faṣlnāmah-i Farhang Mushavirah va Ravān/Darmānī, 2015 از سال 1986 که استینبرگ و سیلوربرگ برای اولینبار اصطلاح استقلال عاطفی را برای جدایی عاطفی نوجوان از والدینشان به کار بردند؛ در رابطه با عوامل تأثیرگذار بر آن، پژوهشهای زیادی صورت گرفت.
asieh omidvar tehrani +1 more
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Nonlinear Canonical Correlation Analysis:A Compressed Representation Approach
Entropy, 2020 Canonical Correlation Analysis (CCA) is a linear representation learning method that seeks maximally correlated variables in multi-view data. Nonlinear CCA extends this notion to a broader family of transformations, which are more powerful in many real ...
Amichai Painsky +2 more
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CoRR, 2015 We introduce canonical correlation forests (CCFs), a new decision tree ensemble method for classification and regression. Individual canonical correlation trees are binary decision trees with hyperplane splits based on local canonical correlation coefficients calculated during training.
Tom Rainforth, Frank D. Wood
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