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Reflections on Random Forests

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If you have a question about this talk, please contact Prof. Julia Gog.

A random forest (RF) is a classifier consisting of a large ensemble of classification trees induced from data. RF induction is one of the most accurate machine-learning algorithms available. I will describe how RF-based classification was used for the prediction of Candida infection in intensive care patients, as well as some of the pros and cons of using RFs.

This talk is part of the Worms and Bugs series.

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