Using accuracy in scientific discovery
Learning by discovery aims at bringing to light laws from a set of numerical or symbolic data. Our work deals with the improvement of the discovery system ABACUS created by Michalski and Falkenhainer, and in particular, with the way the system makes use of informative accuracy of the data. ABACUS, like most others current discovery systems does not use this information in the real physical sense, that means accuracy given by the measure device. However, in experimental domains accuracy cannot obviously be separated from the data. In this paper, we show how, when used in a more realistic manner, this information can significantly improve not only the accuracy of the results but also the efficiency of the search algorithm. Several additional modifications to ABACUS to improve the robustness of the system without losing generality will also be described.
Key-wordsScientific discovery learning by observation numeric — symbolic integration
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