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The drug discovery process can be divided into four subsets, including acquisition of chemical drug candidates, pharmacodynamic testing of large numbers of compounds, and the optimization of pharmacokinetic, and pharmaceutical properties.
The 16 QAM constellation is divided into four subsets: =, =, =, =. = is the constellation for 16 QAM.
A K-fold cross-validation method was used in the training and testing process, and K was set to 4. Using this method, the data set was divided into four subsets, and for each classification, one of the subsets was used as a test set and the other three subsets were combined to form a training set.
The data was divided into four subsets on the basis of the pEGFR-IR and CB1IR scores.
Each group is subsequently divided into four subsets (Table 1).
The 140 pairs of PA and lateral radiographs were divided into four subsets of 35 each.
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Each set was further divided into four subsets of four, with one subset for each modality condition.
For each rock type, data were randomly divided into two subsets, training and test sets.
To do this, the collected data were divided into two subsets, namely the training and testing subsets.
This dataset is randomly divided into two subsets, one for training, the other for testing or validating the model.
The data are divided into two subsets: training set for model calibration and independent validation set for model verification.
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