7. Random Forest in R programming language

Random Forest Algorithm Assumptions

  • There should be some actual values in the feature variables of the dataset, which will give the classifier a better chance to predict accurate results, rather than provide an estimation. Missing values should be handled from training the model.
  • The predictions from each tree must have very low correlations.

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