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Then, log2 ratio between the mixed datasets was calculated.
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Simultaneously, due to dynamic expression across different individuals, equally mixed datasets were also used to estimate the expression patterns.
The predictive abilities using five times 5-fold CV of datasets resulting from first stage analysis of all spatial and non-spatial models plus the mixed datasets were in general very similar within sampling strategies (Table 7).
Measures of imputation success from 50,000 markers, 500,000 markers, and the two mixed density datasets are in Table 1.
Time series, non-time series and mixed type datasets were used as benchmark datasets, and the performance of each algorithm was evaluated using different measures mentioned above.
A framework for classifying mixed-type data in imbalanced datasets was proposed.
This technique is based on the assumption that the source components of the mixed multispectral dataset are statistically independent.
Supplementary File 4 shows that the optimum results for hotspot prediction on 10-fold mixed training dataset were obtained when the EEC is selected as 8.
Though the phylogenetic results based on different datasets are mixed, and support values for some nodes are not high (Fig. 2 4), some conclusions could be drawn following by comparison between our phylogenetic trees and system of Lynn [1].
This was performed separately for human and rat networks, and then the resulting datasets were mixed to improve the fit.
Since across-breed prediction equations performed equally or better than the within-breed prediction equations, and the mixed-breed dataset is likely to grow faster than the pure-breed dataset, we recommend that breeders use prediction equations from the mixed-breed training population.
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