Results 11 to 20 of about 173,823 (243)
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
doaj +1 more source
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.
Hardoon, David R., Shawe-Taylor, John
openaire +3 more sources
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
doaj +1 more source
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
doaj +1 more source
Robust Sparse Canonical Correlation Analysis [PDF]
SSRN Electronic Journal, 2015 Canonical correlation analysis (CCA) is a multivariate statistical method which describes the associations between two sets of variables. The objective is to find linear combinations of the variables in each data set having maximal correlation. This paper discusses a method for Robust Sparse CCA.
Wilms, Ines, Croux, Christophe
openaire +6 more sources
Measuring entrepreneurship determinants: empirical analysis
Agricultural and Resource Economics, 2021 Purpose. The aim of this article is to assess the main determinants that affect entrepreneurial activity, and also the mechanism of its regulation in five countries (Ukraine, Romania, Lithuania, Poland, Germany) during the period from 2007 to 2018 ...
Viktoriia Kyfyak +3 more
doaj +1 more source
Effect of Soil Aeration and Root Morphology on Yield under Aerated Irrigation
Agronomy, 2023 Soil compaction easily causes root hypoxia stress, resulting in poor root growth and the absorption of soil water and nutrients. We hypothesized that aerated irrigation (AI) could enhance nutrient uptake and utilization, thus unlocking the high yield ...
Cuicui Jin +6 more
doaj +1 more source
Permutation inference for canonical correlation analysis
NeuroImage, 2020 Canonical correlation analysis (CCA) has become a key tool for population neuroimaging, allowing investigation of associations between many imaging and non-imaging measurements.
Anderson M. Winkler +3 more
doaj +1 more source
Process Monitoring Using Canonical Correlation Analysis
JISR on Computing, 2019 Principal component analysis (PCA) and partial least square (PLS) used for fault diagnosis and process monitoring for systems. It is expected that the information to be examined isn't self-connected.
Yin SHEN +4 more
doaj +1 more source
Ensemble canonical correlation analysis
Applied Intelligence, 2013 Canonical Correlation Analysis (CCA) aims at identifying linear dependencies between two different but related multivariate views of the same underlying semantics. Ignoring its various extensions to more than two views, CCA uses these two views as complex labels to guide the search of maximally correlated projection vectors (covariates). Therefore, CCA
Sakar, C. Okan +2 more
openaire +2 more sources