Abstract
In this paper, a final version of the rule based classifier (ADX) is presented. ADX is an algorithm for inductive learning and for later classification of objects. As is typical for rule systems, knowledge representation is easy to understand by a human. The advantage of ADX algorithm is that rules are not too complicated and for most real datasets learning time increases linearly with the size of a dataset. The novel elements in this work are the following: a new method for selection of the final ruleset in ADX and the classification mechanism. The algorithm’s performance is illustrated by a series of experiments performed on a suitably designed set of artificial data.
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Dramiński, M. (2016). ADX Algorithm for Supervised Classification. In: Matwin, S., Mielniczuk, J. (eds) Challenges in Computational Statistics and Data Mining. Studies in Computational Intelligence, vol 605. Springer, Cham. https://doi.org/10.1007/978-3-319-18781-5_3
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DOI: https://doi.org/10.1007/978-3-319-18781-5_3
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