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RANDOMFORESTC
W = RANDOMFORESTC(A,L,N)
W = A*RANDOMFORESTC([],L,N)
Input | |
A | Dateset used for training |
L | Number of decision trees to be generated (default 50) |
N | Size of feature subsets to be used (default 1) |
Output | |
W | Resulting, trained feature space classifier |
Train a decision forest on A, using L decision trees, each trained on a bootstrapped version of dataset A. Each decison tree is using random
feature | subsets of size N in each node. When N=0, no feature subsets |
are | used. |
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