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Data distribution pattern (normality) and homogeneity of variances were checked.
The larger the absolute value of the skewness, the larger the skew degree of the data distribution pattern.
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KPCA calculates the mappings of data points and maps the data to another feature space, thus separates the exception points from the normal data distribution patterns.
A non-linear dimensionality reduction method, capable of dealing with highly non-linear data distribution patterns, is investigated in more detail.
The Kolmogorov-Smirnov test was used to determine data distribution patterns.
Data distribution patterns were checked by using scatter plots, and normality and homogeneity of variances were checked by descriptive statistics.
Specifically, similar to the network-based statistics [ 27], our multiple comparisons were corrected based on nonrandom data distribution patterns.
To prove the fact that the ANN model successfully learned the relationship between the four input variables and the density as the output, one within the whole range of the data, the distribution pattern of the relative errors was reported in Figure 9.
For compounds that induce a positive ocular response in the in vivo phototoxicity assay, data on distribution patterns to substructures of the eye can inform decisions regarding the nature of the ocular findings and possibly influence compound advancement.
To assess potential correlations with L_RHI, the Pearson correlation coefficient was used for data with normal distribution pattern, whereas the Spearman rank-correlation coefficient was used for data with a non-normal distribution.
Our data on the distribution pattern of LDH are in agreement with the concept of the metabolic lobulus and are supported by a recent evaluation of the vascular architecture in rat liver.
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