ScienceDirect

• A random forest is a supervised ML classifier that consists of tree-like structure, unique independent vector, and input for most famous class of x

SAS HPFOREST Procedure

https://documentation.sas.com/doc/en/pgmsascdc/9.4_3.5/emhpprcref/emhpprcref_hpforest_toc.htm

Random Forests ~ Leo Breiman(2001)

https://www.stat.berkeley.edu/~breiman/randomforest2001.pdf

Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest.

• the generalization error for forests converges a.s. to a limit
  • as the number of trees in the forest becomes large
• the generalization error of a forest of tree classifiers
  • depends on the strength of the individual trees in the forest
    • and the correlation between them