Based on random forest instance proximity measure detects training cases which are different to all other cases.
a random forest model returned by
a training set used to generate the
Strangeness is defined using the random forest model via a proximity matrix (see
If the number is greater than 10, the case can be considered an outlier according to Breiman 2001.
For each instance from a
dataset the function returns a numeric score of its strangeness to other cases.
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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