Random forest computes similarity between instances with classification of out-of-bag instances. If two out-of-bag cases are classified in the same tree leaf the proximity between them is incremented.
A proximity is transformed into distance with expression
Function returns an M by M matrix where M is the number of training instances.
Returned matrix is used as an input to other function (see
John Adeyanju Alao (as a part of his BSc thesis) and Marko Robnik-Sikonja (thesis supervisor)
Leo Breiman: Random Forests. Machine Learning Journal, 45:5-32, 2001
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