PLANN-CR-ARD model predictions and Non-parametric estimates with Confidence Intervals

This paper investigates the performance of the PLANN-CR-ARD network predictions through a comparison with the confidence intervals and the non-parametric estimates obtained from the survival analysis of a Primary Billiary Cirrhosis (PBC) dataset. The predictions of the PLANN-CR-ARD model are marginalized using two methods: approximation of the integral of marginalization and the Monte Carlo method. The numerical results show that the PLANN-CR-ARD predicts very well, the results being situated within the confidence intervals of the non-parametric estimates. The Model Selection is also performed on the same dataset. The PLANN-CR-ARD can be used to explore the non-linear interdependencies between the predicted outputs and the input data which in survival analysis describes the characteristics of the patients.