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The database is split into three parts: the largest contains profile information, including the names, street addresses, and dates of birth of users.
The database is split into three sets.
In the setting up the classification experiment, the database is split into training and test set.
For properly designing and testing the speech separation system, the database is split into two different subsets, one for design and another for test.
Following [10] the evaluation is performed as follows: (i) the image database is split in a training set (1300 images) and a testing set (700 images); (ii) the embedded message is the same for all the three techniques but it differs among the images.
The database is split in two parts that are processed separately, and when both processors finish execution, the CPU merges the results, and, if desired, carries out a gapped alignment.
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The database was split randomly into five equal-sized file sets, with one set being used as test data and other four for training the system.
In vertical partitioning, some columns of the database are split into groups which are commonly accessed together, improving access locality [9].
The original database was split in two parts, 60% of the data were used for training and 40% for testing the classifier.
The database was split into two parts: 2/3 of the total amount of data, i.e., 16 sessions, for training/development, and the remaining 1/3, i.e., 8 sessions, for testing.
Following this criterion the database was split in: normal (i.e., types Z and O) containing 200 recordings, seizure free (i.e., types N and F) with 200 recordings, and seizure (i.e., type S) with 100 recordings.
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