Sentence examples for variability of the dataset from inspiring English sources

The general strategy for data processing consisted, as a first step, of reducing the extreme complexity and variability of the dataset by identifying more homogenous groups of plots.

The number of end members necessary to best describe the variability of the dataset (that is, the number of factors indicated by the QFA) helps steer the CLS and TI multiple linear regressions.

Additionally, the number of components for PCA/PLS (n for the 1D methods, n r and n C for the 2D methods) were selected based on the number of components that describes the 90% of the total variability of the dataset.

Component loadings for the first three principal components explain only 21% of the variability of the dataset (Figure 3C).

Mapping and interpretation of leachate and bulk chemical composition data is only appropriate if the variability of field duplicate data at individual sampling locations is less than the total variability of the dataset.

Zheng-Bradley et al. conducted a principal component analysis (PCA) on a merged dataset containing gene expression data from mouse and human tissues, in order to capture the factors that mostly account for the variability of the dataset.

A number of factors can influence the behavior of the algorithms, namely the presence of natural drifts and the natural variability of the datasets.

Cross-validation indicates that vigiRank is not over-fitted to sampling variability of the reference dataset: the mean cross-validated AUC is marginally below that for the reference dataset as a whole, the selected predictors and their coefficients are remarkably consistent over the five cross-validation iterations, and vigiRank consistently outperforms IC025 over all iterations.

To use the complete variability of the PIAAC dataset when accounting for field characteristics, path analyses are run on pooled data.

The results show the remarkable advantage that only a few EOFs are required to represent most of the variability of the original dataset, owing to the quick convergence of the EOF series.

Importantly, this threshold must account for the intrinsic variability of the underlying dataset.