In the field of catalysis, there is a growing need to process large and complex datasets. These datasets often come from experiments, simulations, or high-throughput screening methods. SVMs are particularly well-suited for handling such data due to their ability to manage high-dimensional spaces and their effectiveness in scenarios where the number of dimensions exceeds the number of samples.