Sentence examples for original variability from inspiring English sources

d% of the original variability explained by the component.

In the case of the proteasome, this variability is still about 50% of the original variability (Table 2).

However, it should be noted that the 1st and 2nd PC captured only 1.5%and1.4%4% of the total original variability of the SNP data, respectively (Table  3).

This is achieved through an orthogonal transformation of the original dataset such that as much of the original variability as possible is included in the first few PC.

The main advantage of PCR derives from the ability of PCA to capture a large proportion of the original variability of the dataset (e.g. >90%) in a small set of uncorrelated PC.

As a result, using empirical thresholds to select PC for inclusion in the model (e.g. PC that together explain more than 90% of the original variability in the SNP genotypes based on eigenvalues) simply does not result in the highest accuracies that can be achieved in PCR.

These components, which express combinations of the original variables, allow a dimensionality reduction while maintaining as much as possible the variability of the original data.

PCA is a data reduction technique that transforms the original variables into a set of uncorrelated variables (eigenvectors or principal components) in such a way that the first few components encompass most of the variability in the original variables.

Unlike linear regression techniques, GEP does not overpredict mean values and thereby preserves original data variability.

There is a lot of research seeking to understand the "reference" conditions in national parks, she says, which serves as a baseline indicating the original natural variability of ecosystems and providing a guide for ecological restoration elsewhere.

It utilizes the singular value decomposition of the normalized predictors, and allows bigger deviation from zero to the regression parameters of the orthonormalized predictors which are known to explain the original predictor variability most, i.e., have biggest singular values.