Machine Learning Methods Application to Search for Regularities in Chemical Data
The possibility of searching for classification regularities in large arrays of chemical information by means of machine learning methods is discussed. Tasks peculiarities in inorganic chemistry and materials science are considered. The short review of these methods applications to inorganic chemistry and materials science is presented. The system for computer-assisted inorganic compounds design based on machine learning methods has been developed. The developed system usage makes it possible to predict new inorganic compounds and estimate some of their properties without experimental synthesis. The results of this information-analytical system application to inorganic compounds design are promising for new materials search.