'honestRF_R' inherits 'RF', which serves as a modified version of 'RF'. The major change is that it trains honest trees instead of adaptive trees. Adaptive trees are the original trees as they were used in the original implementation and honest trees differ in that they require two data sets to do tree estimation. One data set is used to create the trees and the other one is used to receive the leaf estimates.
Proportion of the training data used as the splitting dataset. It is a ratio between 0 and 1. If the ratio is 1, then essentially splitting dataset becomes the total entire sampled set and the averaging dataset is empty. If the ratio is 0, then the splitting data set is empty and all the data is used for the averaging data set (This is not a good usage however since there will be no data available for splitting).
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