Our machine learning-based property prediction method consists of data preprocessing, modeling, and post-processing. The preprocessing step prepares the raw data for any machine learning model by removing missing and inconsistent information. It also involves feature engineering to reduce the feature space. The best-trained model is used to compute two error types for each observation: