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In addition, we evaluated the performance of each classifier on a seventh independent dataset (Vijver et al. [ 3]). Figure 6A and 6B show the DLCV error and validation error as a function of the number of datasets pooled.
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But as Marshall Kirkpatrick at ReadWriteWeb pointed out, the launch was a bit disappointing in terms of the number of datasets released, only 47 out of thousands and thousands of datasets the US government collects.
This relationship will lead to lower levels of implementation over time in the function of the number of uniform datasets.
Then, the number of datasets (five) was simply determined.
However, the number of datasets to consider of course depends on the heterogeneity of the datasets.
Figure 1 and Figure 2 show the classification accuracy results as a function of the number of selected genes on the seven datasets respectively.
An extensive experimentation with a number of datasets and classifiers as a function of the number of calculations reveals the efficiency of this approach.
Panels show the detected variation as a function of the number of genes used in the between-condition normalization, for the real dataset (a), synthetic dataset with differential gene expression (b), and synthetic dataset without differential gene expression (c).
Figure 4 shows the time required for the sinogram generation and the actual reconstruction for the Highres dataset as a function of the number of cores used.
The fraction of genes joint to the three datasets was compared as a function of the number of top-ranked genes selected.
(a) LCC values for Datasets I and II as a function of the number of blocks, m, with M = 50, 75, 100, and 125.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com