RFNode-class: RFNode Constructor
In theo-s/Rforestry_R: Random Forests

Description Slots

'RFNode' is the basic element inside a 'RFTree'. For each node, it contains the corresponding data that are assigned to the node. The 'RFNode' can be either a leaf or a tree node (non-leaf). If it is a leaf node, 'avgfunc' can be called to aggregate all the observations in the node and save a prediction for the node. If it is a tree node, it will contains 'leftChild' and 'rightChild' which will be another two 'RFNode's. The parent node can be used to track the 'splitFeature' and 'splitValue'. Please note that in the 'RFNode', 'sampleIndex' essentially tells what data reside in the node. Every node contains two 'sampleIndex': 'averagingSampleIndex' and 'splittingSampleIndex'. 'averagingSampleIndex' is used to generate aggregated prediction for the node. 'splittingSampleIndex' is used for 'honestRF' which stores the splitting data when creating the tree. In default, 'RFNode' has the same 'averagingSampleIndex' and 'splittingSampleIndex'.

sampleIndex: A list of index of dataset used in this node and its children. 'sampleIndex' contains two keys 'averagingSampleIndex' and 'splittingSampleIndex'. 'averagingSampleIndex' is used to generate aggregated prediction for the node. 'splittingSampleIndex' is used for 'honestRF' which stores the splitting data when creating the tree. In default, 'splittingSampleIndex' is the same as 'averagingSampleIndex'.
splitFeature: Name of the feature that is used for splitting in this node.
splitValue: The value that is used for splitting in this node.
child: If the node is not a leaf node, the 'child' will be a list of two 'RFNode' objects. If it is a leaf node, the 'child' will be 'NULL'.
nSplit: Number of observations in the splitting dataset in this node.
nAverage: Number of observations in the averaging dataset in this node.