Sentence examples for large principal components from inspiring English sources

After retaining the first t large principal components and leaving out the rest less significant principal components of Ξ s and Γ s, a dimension reduced sub matrix equation is given as follows (14) Γ s t = Ξ s t X.

CPV TH = 90% is used to determine the number of retained large principal components of each sub weight matrix W s. There are almost no visual differences in both three dimensional (3D) views and sections of the results reconstructed from the reduced weight matrix using PCA and the original weight matrix in the two experiments.

We also used sub- scales of the NPI-Q in the analyses, based on a previous large principal component analysis conducted with data from Norwegian nursing home patients [ 23].

Then PCA is applied to the covariance matrix C, and M largest principal components are used for the feature extraction as follows Y i = X i − X ― T D (19).

The GA identifies a set of features (wavelengths) that optimize the separation of the classes in a plot of the two or three largest principal components of the data.

To visualize the high-dimensional trajectories and capture the entire dynamics, we used principle components analysis (PCA) on the gene expression profiles and plotted trajectories in the phase space of the three largest principal components (Fig. 4).

Figure 8 shows the relative co-ordinates of individuals when plotted using the two largest principal components.

Then PCA analysis was performed on the reduced pilot data set and the three largest principal components were selected (i.e., the directions associated with the largest eigenvalues).

By plotting the treatment scores or component loading values derived from PCA in the space defined by the largest principal components, associations between treatments and metabolic components can be revealed.

In our analysis, we chose to retain the three largest principal components for white matter and CSF space respectively as co-variates of no interest in the GLM analysis.

Finally, we used the gene expression values from the independent data set corresponding to the 3000 genes that were previously selected in the pilot data set and projected this reduced independent data set in the space defined by the three largest principal components in the pilot data.