Figure 3

Effect of distance measure choice for ordering and weighting phenotypes. Here we plot for how many diseases the median rank of the gene withheld during leave-one-out cross-validation stays at a certain level, using all available species, and integrating the results using the naïve Bayes scheme. In (a), we vary the distance and weighting function (using the same measure for both). In (b), we show the effect of varying the distance function independently from the weighting function. Here the first function in the legend is the distance function used for computing the k nearest neighbors, and the second is the weighting function w _{i j} from Equations 1 and 4. As can be seen from the figure, a good distance function has more effect on performance than a good weighting function, but that the results can be improved slightly by using a combination: hypergeometric for distance, and Pearson for integration.