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In Figure 2A the average performance of all methods on the ALL dataset is displayed.
The initial dataset is displayed in an n-dimensional space, n being the number of defined variables.
The genome dataset is displayed on two levels (gene and transcript levels) as one gene may have one or more corresponding transcripts.
To investigate this in the context of the PCA study, we plot CVIIM s,n,K against e full, K (s ) in the upper panel of Fig. 4, where the different analysis settings for a given dataset are represented using the same colour and number, and the mean of each dataset is displayed as a black point.
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All 145 chunks forming a single dataset are displayed, showing the range of rotations, translation, skin pattern changes, and variability in lighting and background that can be successfully aligned.
The results of different CENI models on the MemeTracker dataset are shown in Fig. 5, and the results on the Sina Weibo dataset are displayed in Fig. 6.
Summary statistics for the entire dataset are displayed in Table 2, Figure 2 and Dataset S3).
The distinct expression patterns of the first step and second step classifiers in the NCI dataset are displayed in Figures 3 and 4 respectively.
Survival plots generated from each study's dataset are displayed in corresponding sections.
Below the summary of results table, detailed results for each dataset are displayed.
Disease-free survival from 410 cases of validation dataset was displayed in Figures 1(a) and 1(b).
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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