The occurrence model is then extended to a two-dimensional medium by using appropriate two-dimensional variance function for the discrete random field.
Given a bicluster B = g×c, the ith gene variance in B is defined by RVAR i, c) and the overall gene-dimensional variance is defined as the sum of all genes variance as follows.
We hope to mine those biclusters with low mean squared residue, with high volume and gene-dimensional variance, thus three objectives in conflict with each other are used to model multi-objective optimization problem.
Our hope is mining biclusters with low mean squared residue, with high volume and gene-dimensional variance, and those three objectives in conflict with each other are well suited for multi-objective to model.
AIC had better scores for the models that used row and column effects, e.g. Models M9, M6 and M2 (Table 5) or M8 that had a 2-dimensional variance-covariance error structure.
This weakness is mainly caused by its definition of the dimensional global variance, the improved version of which is employed by O-HARP.
This is a three-dimensional mean-variance frontier as the optimal variance now depends on the choice of both a deterministic drift m and a random drift d.
Furthermore, two-dimensional phase-variance data over a selected depth region as well as three-dimensional representation of the vasculature are presented and compared with fundus FA images.
with G = I + F, where n is a K dimensional effective noise variance vector whose k th element is n k = N t σ n 2 μ max ( Ω k, j, 2 ) d k, k − ρ χ k, k, and F k, j = d k, j − ρ χ k, j μ max ( Ω k, j, 1 ) d k, k − ρ χ k, k k ≠ j 0 k = j ; (23).
PCA locates a lower dimensional hyperplane of highest variance in a hyperspace, and projects the data onto the hyperplane.
