Abstract
This chapter discusses a possible way of specializing the generic forest model presented in the previous chapter for the classification task. A number of experiments on toy data are presented in order to provide the reader with some basic intuition about the behavior of classification forests. A small number of exercises is also provided to study the effect of various forest parameters and help the reader to familiarize with the available code.
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Notes
- 1.
As opposed to transductive tasks. The distinction will become clearer later.
- 2.
This effect will be analyzed further in the next section.
- 3.
Analogous to support vectors in SVM.
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Criminisi, A., Shotton, J. (2013). Classification Forests. In: Criminisi, A., Shotton, J. (eds) Decision Forests for Computer Vision and Medical Image Analysis. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-4929-3_4
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