Table 5 Summary of the classifier models that have been used in the two phases of the virtual screening experiment

Phase 1 (binary classification)

Soft voting classifier with 2 underlying models:

Random forest classifier:

 criterion = ‘entropy’; max_features = ‘log2’; n_estimators = 30 

k-nearest neighbors classifier:

 n_neighbors = 28; weights = ‘uniform’

Phase 2 (multiclass)

Extra Trees classifier:

 max_features = None; criterion = ‘gini’; n_estimators = 90; min_samples_leaf = 1