Titlebook: Stream Data Mining: Algorithms and Their Probabilistic Properties; Leszek Rutkowski,Maciej Jaworski,Piotr Duda Book 2020 Springer Nature S

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Springer Nature Switzerland AG 2020

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Decision Trees in Data Stream Mining produced by decision trees are easily interpretable. A decision tree, in fact, divides attribute values space . into disjoint subspaces. The most common decision tree induction algorithms for static data sets are the ID3 algorithm [.], the C4.5 algorithm [., .], and the CART algorithm [.].

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Probabilistic Neural Networks for the Streaming Data Classificationhough there exist a lot of methods for classification of static datasets, they can hardly be adapted to deal with data streams. This is due to the features of the data stream such as potentially infinite volume, fast rate of data arrival and the occurrence of concept drift.