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2; Selected dataset that exclude 4 fake M7 earthquakes from the original dataset in Table 1.
We present the results from the label prediction experiments on TBI dataset in Table 4.
Fig. 2 An example model with CARs for the dataset in Table 1.
We recorded the background images at the same places where we do our dataset in Table 3.
We performed separate analyses on three partitions of the dataset in Table 1: 38-cases by 13-variables full dataset (NIST long-list).
Figure 1 shows the CAP-tree built on the toy dataset in Table 1, with the minimum support threshold set to 0.3, that is 2 records.
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The experiments have been repeated 10 times, and then we report the average scores over different datasets in Table 1.
The datasets in Table 2 were normalised between 0 and 1 using WEKA [52] and contained no missing values.
We provide exemplary values of these parameters for the introduced datasets in Table 2 and describe these parameters in detail below.
We provide qualitative assessments of both the pathological and pathway correspondence between the three datasets in Table 7.
We set and reanalyzed the datasets in Table 1.
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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