I have a dependency treebank including 100 sentences, which I divide into a training set and a test set. I extract some rules ((DS,PS) pairs) to convert the treebank to phrase structures. When I extract such rules from the training set, I can measure the percentage of rules (DS patterns) that cover the test set, suppose
(10, 24%), (20, 34%), (30,40%), (40,44%), (50, 55%),(60, 58%), (70, 61%)...
As you see as I increase the size of the training set, the coverage of extracted patterns increases! however its not linear!, I want to see how many data I need to reach 100% coverage? I guess I can use a regression, but which regression? logarithmic?
Is this related to 'learning curve'? if yes how can I use regression for a learning curve?