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The regions for accepting the null hypothesis that "the differences in parameters between two different subsets of the same landslide dataset are derived from stochastic processes" are shown in Figs. 5 and 6 for γ and R, respectively.

> Prediction results of the six classification engines are provided in Table 4. AUC and accuracy, i.e. 1-misclassification error, on the training dataset are derived from 10-fold cross-validation tests, SD is provided in parentheses.

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The WageIndicator dataset is derived from a web survey on work and wages that is posted on all national WageIndicator websites and is comparable across all countries.

The third dataset is derived from the Port of Antwerp and contains very detailed information on the origin and destination of the container flows.

The third dataset is derived from ECMWF data and has a temporal resolution of up to four times a day and a spatial resolution of 0.25° × 0.25°.

Fig. 5 The regions of acceptance for the null hypothesis that "the observed differences in power exponent between two different subsets of the same dataset is derived from random processes" at a significance level of 0.05 are shown.

The dataset is derived from photos on Flickr and is used in machine learning for training and testing purposes.

The "linked" dataset was derived from sequences from acutely infected individuals and known transmission pairs.

Our kinase dataset is derived from KinG (version 1.5) and has information for only for 303 prokaryotic genomes.

A 'representative' dataset was derived from the aligned genome dataset; it consisted of 47 sequences, one genome from each potyvirus species.

The last dataset is derived from IntAct [18] by using interactions that are described as 'Physical interactions' in the field 'Interaction type'.

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