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Liste der Ergebnisse
- Active Learning for experimental exploration + (A ranking is the result of running an expe … A ranking is the result of running an experiment, a set of encoders is applied to an</br>experimental condition (dataset, model, tuning, scoring) and are then ranked according to</br>their performance.</br>To draw conclusions about the performance of the encoders for a set of experimental</br>conditions, one can aggregate the rankings into a consensus ranking. (i.e. taking the median</br>rank)</br>The goal of the thesis is to explore the space of consensus rankings and find all possible</br>consensus rankings.</br>However, running an experiment is a very time-consuming task. Therefore we utilize Active</br>Learning, to avoid running unnecessary experiments. In Active Learning, the learner can</br>choose the data it is trained on and achieves greater accuracy with fewer labeled data. greater accuracy with fewer labeled data.)