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The third dataset is from a fast event-related experiment with two categories of visual objects.
To obtain evaluation statistics, fitted models were then applied to the third dataset (e.g. dataset III).
For the third dataset (UAH-DriveSet), an accuracy of 76% is achieved using only GPS data.
The third dataset (CCD_gen) brings further complexity, since it contains heterogeneous types of molecules.
The third dataset is DBGen [20], a synthetic data set obtained from the authors of a previous algorithm [7].
The tweets in the third dataset are a uniformly sampled subset of our environmental tweets, therefore highly domain-specific.
In addition, the third dataset is used to simulate actual virtual screening process against a large pharmaceutical database.
The third dataset is derived from the Port of Antwerp and contains very detailed information on the origin and destination of the container flows.
For the third dataset, moderately active structures were used as queries to search an anti-HIV database of active and inactives.
Tweets were collected in September and October of 2015 for the first two datasets, and in October and November of 2016 for the third dataset.
The third dataset, the anti-HIV dataset from the National Cancer Institute, is employed to simulate a typical virtual screening experiment.
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