Abstract
In Chapter 4, we looked at the process of building a decision tree. Decision trees can overfit on top of the data in some cases—for example, when there are outliers in the data. Having correlated independent variables may also result in the incorrect variable being selected for splitting the root node.
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© 2018 V Kishore Ayyadevara
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Ayyadevara, V.K. (2018). Random Forest. In: Pro Machine Learning Algorithms . Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-3564-5_5
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DOI: https://doi.org/10.1007/978-1-4842-3564-5_5
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