Sentence examples for big datasets are from inspiring English sources

Big datasets are becoming more prevalent in modern statistics.

Big datasets are often stored in flat files and can contain contradictory data.

Pairwise comparisons for big datasets are computationally infeasible to sufficiently estimate p-values with enough accuracy to protect against false positives.

For example, understanding the differences between the vast majority of users (i.e. humanity) and smaller subsets of people, whose activities are captured in big datasets, is critical to correct analysis of the data.

By contrast, a big dataset is designed to be re-used for many purposes, and to answer multiple questions including questions that cannot be anticipated at the time of data collection.

With the advancement of comparatively inexpensive and high throughput technologies bigger dataset are increasingly common nowadays.

However, the analysis of large datasets is complicated, and significant amounts of information stay hidden in big data.

One must be careful in assuming that any large dataset is a big data.

Moreover, successful applications in big medical datasets are expected to dramatically scaling up MCMAR for complex infant brain MRI in terms of efficiency and feasibility.

Moreover, there are other fMRI big datasets that are publicly available for researchers such as OpenfMRI [21] and human connectomes project (HCP) [22].

Cross domain alignment can give us a multi side view to domains, but it costs on time and when the datasets are as big as real-life workflows data it exhibits its expensiveness so we utilize Transfer learning to reduce the middle process sequences time of the cross domain workflow alignment.