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Applying machine learning techniques to predict the properties of energetic materials
- D. Elton, Zois Boukouvalas, Mark S Butrico, M. Fuge, P. W. Chung
- Materials Science, Computer Science
- Scientific Reports
- 15 January 2018
This work presents a comprehensive comparison of machine learning models and several molecular featurization methods - sum over bonds, custom descriptors, Coulomb matrices, Bag of Bonds, and fingerprints - and concludes that the best featurizing was sum over bond counting, and the best model was kernel ridge regression. Expand