Sentence examples for the big datasets from inspiring English sources

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.

Given such prior information, sequential design is undertaken as a way of identifying informative data to extract from the big dataset.

Then the big dataset provides a less reliable estimate of the overall percentage of Trump voters than a simple random sample of just 450 people, where responses are accurate.

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.

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 small dataset represents the General-100 dataset, which contains 100 images, while the big dataset represents our new established dataset that contains 260 images.

Bonferroni correction was also used for BEAM on the big dataset.

On the big dataset, the single-locus χ test was performed on the data with background noise and power using both Bonferroni correction and permutation tests was recorded.

We used a dataset of 1390 genomes (the "big" dataset) and a randomly selected subset of 100 genomes (the "small" 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.