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Given such prior information, sequential design is undertaken as a way of identifying informative data to extract from the big dataset.
The small dataset represents the General-100 dataset, which contains 100 images, while the big dataset represents our new established dataset that contains 260 images.
As in Drovandi et al. (2015), we argue that this can be obtained in big data settings through the use of an initial learning phase where data are extracted from the big dataset such that appropriate models for analysis can be explored and prior distributions of parameters can be formed.
The experimental results on a multi-node cluster show that the proposed parallel algorithms with granularity control are the powerful tools to process the big dataset and the parallel D8 algorithm is insensitive to granularity, while the parallel AreaD8 algorithm has an optimal grain size to reap the best parallel performance.
Bonferroni correction was also used for BEAM on the big dataset.
We chose to use 200 trees for the comparison with RF on the small dataset and 1000 trees for the comparison with BEAM on the big dataset.
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The New York Times, a leading US newspaper, reports that data scientists spend 50 80% of the time on cleaning the big datasets [30].
It has been a long history that intelligent methods from artificial intelligence were widely used in bioinformatics, where these approaches were utilized to analyze and interpret the big datasets that cannot be handled by biologists.
For the bigger dataset DTP_large, which contains more atom types, differences between the tested approaches started to appear.
"When each developer gives some examples, Wit understands and connects that example to others like it, and those new phrases become part of the bigger dataset".
In the biggest dataset (the last subset of Reference 9), T-Coffee took more than nine days to complete the alignment.
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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