Where 𝑛 is the number of samples (50 for testing), 𝑦 𝑖 is the target value and 𝑦 𝑖 ̂ is the predicted value. An Adapting Boosting, AdaBoost , ensemble method was used in combination with the random forest regressor to predict the 7 output properties. The AdaBoost algorithm combined with random forest regressor as weak learning has been previously used in different regression problems showing minor errors and strong predictability capacity. Details of the ML architecture and parameters are shown in Figure .