Topological applications of multilayer perceptrons and support vector machines in financial decision support systems

Abstract The heart of this study is particularly on risk assessment of financial decision support systems (FDSSs), to advance the model performance and improve classification accuracy. To conquer the downsides of the classical models, statistical intelligence (SI) technologies, for example, multilayer perceptrons (MLPs) and support vector machines (SVMs), have been deliberated in FDSS applications. Recently, the prestigiousness of SI approaches has been confronted by the latest prediction learners. Therefore, to ensure the competitive performance of SI mechanisms, the current investigation scrutinizes the topological applications of MLPs and SVMs over eight different databases with equivalent combinations in credit scoring and bankruptcy predictions example sets. The experimental results reveal that MLP 5 ‐5 and MLP 4 ‐4, that is, the sigmoid activation…