Abstract
Decision tree is probably the most intuitive data classification and prediction method. It is also used frequently. While most of the data mining methods we have learned are parametric, decision tree is a rule-based method. The most critical concept in understanding decision trees is entropy which will be explained soon. A tree is composed of nodes and the leaves are the bottom nodes. At each node except for the leaf nodes, a decision must be made to split the node into at least two branches. Figure 9-1 depicts a sample decision tree structure.
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© 2020 Hong Zhou
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Zhou, H. (2020). Decision Trees. In: Learn Data Mining Through Excel. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-5982-5_9
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DOI: https://doi.org/10.1007/978-1-4842-5982-5_9
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Publisher Name: Apress, Berkeley, CA
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Online ISBN: 978-1-4842-5982-5
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