Catalysis research often involves categorical variables such as types of catalysts, substrates, and solvents. Machine learning models require numerical input, making it necessary to convert these categorical variables into a numerical format. One hot encoding helps in maintaining the uniqueness of each category without imposing any ordinal relationship.
