Definition
A random forest is an Ensemble of random Decision Tree classifiers, that makes predictions by combining the predictions of the individual trees. There are different approaches to introduce randomness in the decision tree construction method. A random forest can be used to make predictions over nominal (Classification) or numeric target attributes (Regression). Random forests are one of the best performing predictive models.
Characteristics
Random Forest Construction
The term random forests has been introduced by Breiman (2001), and is a collective term for decision tree ensembles in which each tree is constructed using some random process. Different random forests differ in how the randomness is introduced in the tree building process. In Bagging (Breiman 1996), randomness is introduced by constructing each tree using a bootstrap sample of the Training Set. The randomized outputs method (Breiman 1999) randomly permutes the target attributes before constructing the trees....
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Vens, C. (2013). Random Forest. In: Dubitzky, W., Wolkenhauer, O., Cho, KH., Yokota, H. (eds) Encyclopedia of Systems Biology. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9863-7_612
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DOI: https://doi.org/10.1007/978-1-4419-9863-7_612
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