rfProximity {CORElearn} | R Documentation |
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.
rfProximity(model, outProximity=TRUE)
model |
a |
outProximity |
if |
A proximity is transformed into distance with expression distance=sqrt(1-proximity)
.
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 rfOutliers
and rfClustering
).
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
CoreModel
,
rfOutliers
,
cmdscale
,
rfClustering
.
md <- CoreModel(Species ~ ., iris, model="rf", rfNoTrees=30, maxThreads=1) pr <- rfProximity(md, outProximity=TRUE) # visualization require(lattice) levelplot(pr) destroyModels(md) # clean up