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To simulate the prediction task, the edges for each ADR node were divided into 10 folds.
The resulting copolymer was isolated as a pink powder (0.60 g) after dissolving in DCM and precipitating into 20-fold MeOH for three times (The PS copolymer: Mn = 7900 g/mol, Đ = 1.07).
Divide the dataset L' pseudo-randomly into V2 folds iv.
The training set is split randomly into 10 folds.
The whole dataset was split into 6 folds by stratified sampling of the pIC50 values.
First, the Kt:p-target dataset was randomly divided into 10 folds.
Step 1. Select number of variables 1. Divide the dataset D pseudo-randomly into V1 folds 2.
The rating database was randomly divided into 10-folds, where each fold contained at least one interaction of each user.
The process of cross-validation begins with the random division of the dataset into 10-folds of compounds.
In the 10-fold cross-validation, data was divided into 10-fold of equal sizes before performing 10 iterations of training and validation.
Divide the dataset D pseudo-randomly into V2 folds making sure that each fold contains the same proportion of each of the Y strata.
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