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For each group of patients, the selected dataset was divided into two parts: one for feature selection and the other for 10-fold cross-validation.
jModeltest software was employed for selection of the best fitted evolutionary model to be used on the selected dataset, with an additional three subtype A1 sequences (accession numbers AB098332, AB253421, AB285785), selected to root the obtained maximum likelihood (ML) tree [ 18, 19].
We made sure the selected dataset covered points from most sub-clusters.
The selected dataset is named after CODE (ftp://ftp.unibe.ch/aiub/CODE).ch/aiub/CODE
The average error is about 0.281 % and the maximum error is about 1.365 % for the selected dataset.
The selected dataset consists of 51 folios which correspond to 20,722 connected components (almost 500 CCs on each folio).
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Finally, we have showed the effectiveness of the proposed identification attack on the selected datasets.
The selected datasets include MSR Action [22], CASIA [23], INRIA [24], Weizmann [25], KTH [25], UIUC [26], and Muhavi [27].
Furthermore, the number of parties varies among the selected datasets while the same happens for the population's distribution percentage among the various parties.
The proposed algorithm provides superior performance for the selected datasets than the robust and widely used ARIMA methodology in predicting time series data.
We have tested our approach on five classical datasets publicly available from UCI website.1 The selected datasets are briefly described in Table 3.
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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