Parent data were split into lower and higher BAP groups.
The data were split into three categories: training of the algorithms (685 patients), validation (172 patients) and test (150 patients).
This was a "three color" image of the Crab Nebula, where the X-ray data were split into three different energy bands.
To do this, data were split randomly into a training and a test sets, then the model was trained with the training sample and its performance was assessed using the test sample.
Furthermore, the data were split into two equal-sized training and test subsets by the Kennard-Stone design and the errors of calibration (RMSEC) and prediction (RMSEP) were calculated.
The data were split randomly into train and test subsets.
The available Pfizer data were split into two categories: IC50 and percent inhibition data.
The data were split into two categories: 1) remarks on the items and 2) remarks on the questionnaire in general.
The corpus data were split into 64 MB blocks (Hadoop default), and loaded into the Hadoop Distributed Filesystem (HDFS).
Data were split into two time frames of 30 min each, and images were reconstructed as described above.
However, very often the discontinuities are not known or cannot be quantified and in these cases the observatory data were split into two or more series.
