Background: Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique fo...
Gift Nyamundanda, Lorraine Brennan, Isobel Claire ...
In document analysis, it is common to prove the usefulness of a component by an experimental evaluation. By applying the respective algorithms to a test sample, some effectiveness...
This paper presents an asymptotic analysis of the eigen value decomposition (EVD) of the sample covariance matrix associated with independent identically distributed (IID) non nec...
With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem...
Component interoperability is the ability of two or more components to cooperate despite their differences in functional and non-functional aspects such as security or performanc...
Sam Supakkul, Ebenezer A. Oladimeji, Lawrence Chun...