Table 2. Comparison of the linear filter with SVD for an increasing fraction of randomly assigned false negatives (FN) for four datasets.

The AUC is given for both the original dataset and a binarized version. Each performance is an average of 100 repetitions. In most cases the linear filter is better than SVD. The performance of the latter deteriorates quickly with an increasing number of false negatives. The performance of the linear filter remains relatively high, even with 90% of false negatives.