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Tutorial on PCA and approximate PCA and approximate kernel PCA
Artificial Intelligence Review, 2022 AbstractPrincipal Component Analysis (PCA) is one of the most widely used data analysis methods in machine learning and AI. This manuscript focuses on the mathematical foundation of classical PCA and its application to a small-sample-size scenario and a large dataset in a high-dimensional space scenario.
Sanparith Marukatat
exaly +2 more sources
Singular Learning of Deep Multilayer Perceptrons for EEG-Based Emotion Recognition
Frontiers in Computer Science, 2021 Human emotion recognition is an important issue in human–computer interactions, and electroencephalograph (EEG) has been widely applied to emotion recognition due to its high reliability.
Weili Guo +6 more
doaj +1 more source
Canadian Journal of Statistics, 2023 AbstractMahalanobis distance of covariate means between treatment and control groups is often adopted as a balance criterion when implementing a rerandomization strategy. However, this criterion may not work well for high‐dimensional cases because it balances all orthogonalized covariates equally.
Hengtao Zhang +2 more
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Melissopalynology analysis, determination of physicochemical parameters, sugars and phenolics in Maltese honey collected in different seasons [PDF]
Journal of the Serbian Chemical Society, 2022 Malta, a country renowned for its honey, has not been extensively mentioned in studies based on honey. In addition to many parameters, the collection period affects honey quality, precisely due to the different floral composition that exists during a ...
Bugeja Douglas Adrian +9 more
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Journal of Statistical Physics, 2017 A system with many degrees of freedom can be characterized by a covariance matrix; principal components analysis (PCA) focuses on the eigenvalues of this matrix, hoping to find a lower dimensional description. But when the spectrum is nearly continuous, any distinction between components that we keep and those that we ignore becomes arbitrary; it then ...
Bradde, Serena, Bialek, William
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Bazı Tescilli Nohut Çeşitlerinin Elek Analiz Değerleri
Turkish Journal of Agriculture: Food Science and Technology, 2021 Ülkemizde nohut hem yaş hem de kuru olarak farklı süreçlerden geçerek tüketilmektedir. Tüketimde tercihen iri taneli nohutlar tercih edilirken 6 mm elek altı genellikle tercih edilmemektedir.
Hamdi Özaktan
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H2Open Journal, 2022 Due to the depletion of natural resources including land and water as a result of rapid population increase, industrialisation, and urbanisation, effective resource management is essential for long-term development. The Kinnerasani Watershed in Telangana
Padala Raja Shekar, Aneesh Mathew
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Experimental investigation of 50 MPa reinforced concrete slabs subjected to blast loading
Ingeniería e Investigación, 2018 This paper presents results from blast tests conducted on four 50 MPa concrete slabs with reinforcement ratios of 0,175% and 0,37%. Two of the slabs were retrofitted with 50 mm thick foam in order to investigate the potential of using the foam as a ...
Fausto Mendonça +2 more
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RKF-PCA: Robust kernel fuzzy PCA
Neural Networks, 2009 Principal component analysis (PCA) is a mathematical method that reduces the dimensionality of the data while retaining most of the variation in the data. Although PCA has been applied in many areas successfully, it suffers from sensitivity to noise and is limited to linear principal components.
Computer and Information Science and Engineering, University of Florida, United States ( host institution ) +3 more
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Tangent Phylogenetic PCA [PDF]
, 2023 Phylogenetic PCA (p-PCA) is a version of PCA for observations that are leaf nodes of a phylogenetic tree. P-PCA accounts for the fact that such observations are not independent, due to shared evolutionary history. The method works on Euclidean data, but in evolutionary biology there is a need for applying it to data on manifolds, particularly shapes ...
Akhøj, Morten +2 more
openaire +4 more sources