Data mining methods often include matrix inversion tasks. Big data mining requires fast and accurate inversion of high-dimensional arrays. The presented work describes the concept of stepwise matrix inversion using the basis exchange algorithm based on the Gauss-Jordan vector tra...
Open access
Research Article10.9734/jamcs/2022/v37i130429
The eigenvalue problem plays an important role in contemporary methods of exploratory data analysis. As an example, the principal component analysis (PCA) widely used in data exploration, is based on finding the eigenvalues and eigenvectors of the covariance matrix. The paper pr...
Open access
Research Article10.9734/JAMCS/2017/33436
Data exploration tasks often require inversion of large matrices. The paper presents a new method of matrices inversion, which uses the basis exchange algorithm controlled by the convex and piecewise linear (CPL) inversion criterion function. Using basis exchange algorithms might...
Open access
Research Article10.9734/BJMCS/2017/31778