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MultivariateRandomForest (version 1.1)

build_single_tree: Model of Single tree of Random Forest or Multivariate Random Forest

Description

Build the model of a tree of RF or MRF using the training samples, which is used for the prediction of testing samples

Usage

build_single_tree(X, Y, mtree, min_leaf, V_inv, Command)

Arguments

X
Input Training matrix of M x N, M is the number of training samples and N is the number of features
Y
Output Training response of M x T, M is the number of samples and T is number of ouput Features(Response)
mtree
Number of randomly selected features used for each split
min_leaf
Minimum number of samples in the leaf node
V_inv
Covariance matrix of Output Feature matrix
Command
1 for RF and 2 for MRF depending on the method

Value

Model of single tree of the forest(RF or MRF)

Details

The Model contains the list of lists, where each list contains either the splitting criteria of a split in a node or, output feature matrix of the samples of a node depending upon which node the list is representing.