Introduction
Decision trees are suitable for scientific problems entail labeling data items with one of a given, finite set of classes based on features of the data items. Decision Trees are classifiers that predict class labels for data items [3]. A decision tree learning algorithm approximates a target concept using a tree representation, where each internal node corresponds to an attribute, and every terminal node corresponds to a class[5][6][10].
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Grosan, C., Abraham, A. (2011). Decision Trees. In: Intelligent Systems. Intelligent Systems Reference Library, vol 17. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21004-4_11
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