They are shown in the figure 3, which shows that, actually, after using only 1% of the training data (4,947 instances), the classifiers already perform very well, and adding more training data improves the results only slightly.
for RIPPER, adding more data causes a decrease in performance, and as we mentioned earlier, even an impossibility of building a classifier.