High dimensional data refers to datasets that have a large number of variables or features. In the context of catalysis, this can include various parameters such as temperature, pressure, concentrations of reactants, and properties of catalysts. These parameters can interact in complex ways, making it challenging to understand and optimize catalytic processes.
