Abstract
In the previous chapters, we’ve considered regression-based algorithms that optimize for a certain metric by varying coefficients or weights. A decision tree forms the basis of tree-based algorithms that help identify the rules to classify and forecast an event or variable we are interested in. Moreover, unlike linear or logistic regression, which are optimized for either regression or classification, decision trees are able to perform both.
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© 2018 V Kishore Ayyadevara
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Ayyadevara, V.K. (2018). Decision Tree. In: Pro Machine Learning Algorithms . Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-3564-5_4
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DOI: https://doi.org/10.1007/978-1-4842-3564-5_4
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Publisher Name: Apress, Berkeley, CA
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