We train the EANN models using only the energies of the water clusters without forces, since the force data is hard to obtain at CCSD(T) level of theory. Within the training set, 10 percent of the data points were used for testing during the training process, while the rest are used for fitting. The network was trained using the hybrid extreme machine learning and Levenberg-Marquardt (ELM-LM) algorithm, and it contains two hidden layers with 60 neurons for each input and hidden layer. In each fitting, the optimization was run for 5000 iterations in each epoch until the variation of the loss function is below 8 10for six consecutive steps, which usually needs 20-30 epochs.