Sentence examples for dataset draws from from inspiring English sources

In contrast, our own dataset draws from the strength of not only fine-grained longitudinal data (order of minutes, nearly complete contextual logging) but also from significant improvements to Bluetooth proximity [19], detailed survey/metadata monitoring from social networks (Facebook, contact lists), and survey data (alter disambiguation, etc).

Our dataset, drawn from a qualitative study of computer use in general practice, comprised background documents, field notes, interviews, clinical consultations (directly observed and videotaped) and naturally occurring talk relating to referral to hospital in four general practices.

We test this model on a novel dataset drawn from a variety of countries in the 2009 and 2014 European Parliament elections.

If there is an available dataset drawn from a target domain of interest that has a different feature space from another target dataset (also drawn from the same target domain), then heterogeneous transfer learning can be used to bridge the difference in the feature spaces and build a predictive model for that target domain.

The expected value of each datum xi in the raw dataset (drawn from an NB distribution with parameters m and k) is reduced to (1−pu ) xi, and the resulting distribution is NB with parameters (1−pu ) m and k (as argued under the topic of 'population-wide control measures' by Lloyd-Smith et al. [8]).

The study population comprises a multi-country dataset drawn from the World Health Survey (WHS).

A merged dataset drawn from the Kenya Demographic and Health Surveys of 1993, 1998 and 2003 was used.

We aimed to estimate the effect of HC use on the risk of HIV acquisition using a large dataset drawn from the MDP301 phase 3 microbicide trial.

"We can now answer questions using very large datasets," drawn from the genetic analyses of hundreds of people and from electrophysiological experiments measuring the output from many neurons synchronously, in real time.

RF leverages the wisdom of crowds by using a forest consisting of multiple stochastically different trees, each based on separately sampled datasets drawn from a common pool of data.

This analysis is a multivariate method that maximizes shared structure among multiple datasets drawn from the same samples.