Abstract
It is known that in decision trees the reliability of lower branches is worse than the upper branches due to data fragmentation problem. As a result, unnecessary tests of attributes may be done, because decision trees may require tests that are not best for some part of the data objects. To supplement the weak point of decision trees of data fragmentation, using reliable short rules with decision tree is suggested, where the short rules come from limited application of association rule finding algorithms. Experiment shows the method can not only generate more reliable decisions but also save test costs by using the short rules.
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Sug, H. (2006). Using Reliable Short Rules to Avoid Unnecessary Tests in Decision Trees. In: Gelbukh, A., Reyes-Garcia, C.A. (eds) MICAI 2006: Advances in Artificial Intelligence. MICAI 2006. Lecture Notes in Computer Science(), vol 4293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11925231_57
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DOI: https://doi.org/10.1007/11925231_57
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