Here is a short report about the results of active learning experiments in effort estimation.
For full plots, refer here.
The moral of the story is:
1) When using 1NN as estimation method, (more or less) half of the instances are not closest neighbor to any other instances.
2) When project instances are labeled by an expert based on their popularity, MdMRE values very easily drop below regular 1NN (with LOO).
3) ASSUMPTION/CHEAT is that the expert perfectly predicts the project effort, which is (probably) never the case.