Fighting Knowledge Acquisition Bottleneck with Argument Based ...
1. Fighting Knowledge Acquisition Bottleneck with Argument Based Machine Learning Martin Mozina, Matej Guid, Jana Krivec, Aleksander Sadikov and Ivan Bratko ECAI 2008 Faculty of Computer and Information Science University of Ljubljana, Slovenia
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12. Knowledge Acquisition of Chess Concepts used in a Chess Tutoring Application Case Study: Bad Bishop
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22. Classification Accuracy Through Iterations Results on the final dataset Method CA Brier score AUC Decision trees ( C4.5) 89% 0,21 0,86 Logistic regression 88% 0,19 0,96 Rule learning (CN2) 88% 0,19 0,94 ABCN2 95% 0,11 0,97
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24. Advantages of ABML for Knowledge Acquisition explain single example easier for experts to articulate knowledge more knowledge from experts critical examples expert provide only relevant knowledge time of experts' involvent is decreased
25. Advantages of ABML for Knowledge Acquisition counter examples detect deficiencies in expert's explanations even more knowledge from experts arguments constrain learning hypotheses are consistent with expert knowledge hypotheses comprehensible to expert more accurate hypotheses