Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
— To approximate complex data, we propose new type of low-dimensional “principal object”: principal cubic complex. This complex is a generalization of linear and nonlinear pr...
Alexander N. Gorban, Neil R. Sumner, Andrei Yu. Zi...
Abstract. Multidimensional data projection and visualisation are becoming increasingly important and have found wide applications in many fields such as decision support, bioinform...
Fuzzy c-varieties (FCV) is one of the clustering algorithms in which the prototypes are multi-dimensional linear varieties. The linear varieties are represented by some local prin...
Covariances from categorical variables are defined using a regular simplex expression for categories. The method follows the variance definition by Gini, and it gives the covaria...