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I'm new with Random forests Classification algorithm, and I have some questions about concepts confused me,

  1. What is the role of prototypes in the classification operation, Are they the core of the classification process, Are they represent the model of the classification.
  2. I have read that Random forests support the replacing of missing variables, Is that mean, If I have a 15 variable then I could pass 13 variable, and the model, which is build by Random forests will find an approximation for the missing two variables?
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(1) The prototypes function is used for when RF are used for clustering (unsupervised learning) rather than classification.
(2) Not all implementations support missing values. RF can support missing values - not variables.

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