The All Relevant Feature Selection using Random Forest

@article{Kursa2011TheAR,
  title={The All Relevant Feature Selection using Random Forest},
  author={Miron B. Kursa and Witold R. Rudnicki},
  journal={ArXiv},
  year={2011},
  volume={abs/1106.5112}
}
In this paper we examine the application of the random forest classifier for the all relevant feature selection problem. To this end we first examine two recently proposed all relevant feature selection algorithms, both being a random forest wrappers, on a series of synthetic data sets with varying size. We show that reasonable accuracy of predictions can be achieved and that heuristic algorithms that were designed to handle the all relevant problem, have performance that is close to that of… CONTINUE READING
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