Predicting marital dissolutions using radial basis function neural networks

Marital dissolutions, that include divorces and separations, are considered one of the most adverse events that can influence the health, life quality and welfare of the adults and infants implied. There have been several researches in the sanitary and sociological field that show how these processes of breaking a life in common can deteriorate the health in both, the physic and the psychological, aspect. This paper presents the application of machine learning methods to be able to predict if a marriage, that has started a dissolution process, will end up in a friendly agreement or it will be taken to the court. In order to accomplish this task, Radial Basis Function Neural Networks in combination with Mutual Information will be able to determine which elements should be considered to make a prediction. As the experiments will show, the methodology applied is able to classify with a high accuracy and robustness a real data base. The results could be applied in order to prevent some traumas to the people involved in the dissolution in the medical aspect and to perform a better management in the legal aspects.