To determine the sensitivity of density of the data set we carried out an experiment where we varied the value of x from 0.2 to 0.9 in an increment of 0.1. For each of these train/test ratio values we ran our experiments using the two prediction generation techniques-basic weighted sum and regression based approach. Our results are shown in Figure 5. We observe that the quality of prediction increase as we increase x. The regression-based approach shows better results than the basic scheme for low values of x but as we increase x the quality tends to fall below the basic scheme. From the curves, we select x=0.8 as an optimum value for our subsequent experiments.